124 results about "Cell based" patented technology

The invention relates to the technical field of computational mechanics and geological disaster simulation, and discloses a full-process numerical simulation method suitable for simulating continuous medium damage to discontinuous medium movement. The invention provides a novel chain-type disaster simulation method for solving the problems that calculation efficiency and large deformation precision are difficult to consider at the same time and the evolution process of a slope from a continuum to a fragmented body cannot be dynamically reflected in the prior art. The core of the method is that a dynamic criterion is set based on a unit real-time damage variable, a failed finite element (FEM) unit is adaptively converted into smoothed particle hydrodynamics (SPH) particles, and the physical state of the particles is accurately mapped; and a virtual particle coupling algorithm is adopted to process a two-domain interface, so that bidirectional transmission of mechanical parameters is realized. The method is executed circularly, the whole process of'continuous deformation-fragmentation flow 'of the side slope is simulated dynamically, high-precision integrated simulation of a'seismic source-propagation-response-movement' disaster chain in the same frame is achieved, and an efficient tool is provided for disaster risk assessment and prevention and control.

The invention discloses a super capacitor monomer health state estimation method based on charging and discharging data, which belongs to the technical field of measurement, and comprises the following steps: carrying out de-noising processing on circulating charging and discharging data of a tested super capacitor monomer, calculating instantaneous frequency and instantaneous energy of the charging and discharging data after de-noising; energy feature distribution of time domain and frequency domain decoupling of the de-noised charging and discharging data is obtained, an energy feature distribution decomposition result is synchronously input into the health state estimation model based on the convolutional neural network, and the real-time capacity and the maximum capacity of the measured super capacitor monomer are fed back to the health state estimation model. And obtaining a predicted value of the capacity of the tested super capacitor monomer after training, and estimating the health degree of the super capacitor monomer. According to the method, collaborative analysis is carried out by fusing the time-domain dynamic characteristics and the frequency-domain steady-state characteristics of the charging and discharging data of the supercapacitor monomer, the limitation of traditional single-dimensional data representation can be broken through, and the detection sensitivity of the degradation phenomenon of the lithium ion supercapacitor is improved.

The invention discloses a cell interaction identification method based on cell space transcriptome data, which comprises the following steps: constructing cell pairs according to cell space proximity, and calculating an interaction signal matrix and space information of each pair of cells by combining a ligand-receptor database; then generating cell pair embedding representation by using a graph neural network, calculating the similarity between cell pairs, and calculating the similarity between cells based on a gene expression matrix; updating the similarity matrix through iteration until convergence to obtain a final similarity matrix between cells and between cell pairs; and clustering the similarity matrix, and constructing a cell type and cell pair type model, thereby realizing accurate cell interaction identification. According to the method, space and expression information can be fully utilized, inter-cell heterogeneity and context specificity interaction can be captured, the analysis precision and biological authenticity of a cell communication network are improved, and an effective tool is provided for research on tissue development, disease mechanisms, immune response and the like.

The invention relates to the technical field of medical information processing, in particular to a cervical cancer cell early screening and intelligent evaluation system based on multi-modal data, which comprises a data acquisition module, a form detection module and a screening early warning module, the data acquisition module is used for acquiring multi-modal data of a current detection object in a plurality of inspection processes; the morphology detection module is used for calculating a cellular morphology score of a current detection object in any target inspection process; the screening early warning module is used for determining similar detection objects of the current detection object, and correcting differences between the current detection object and the similar detection objects in the aspects of cellular morphology scores and lesion detection indexes according to the approximation degree between different types of lesion detection indexes of the current detection object; and obtaining the screening early warning coefficient of the current detection object by using the relative change condition of the correction result. According to the invention, the early screening and evaluation effects on cervical cancer cells are improved.

The invention belongs to the technical field of crossing of rock soil, geological engineering and computer modeling, and discloses a three-dimensional fractured rock anisotropic fragmentation and expansion structure generation method and system, and the method comprises the following steps: generating tightly embedded initial blocks in an expansion domain according to the number of control blocks and the initial equivalent size of the blocks; on the basis of the node information of the initial block, anisotropic fragmentation and expansion mapping geometric transformation is carried out on the cell elements, and node coordinate information after fragmentation and expansion and form control is carried out is obtained; calculating the volume ratio of blocks in the target area to obtain a current volume fraction; extracting a target domain in the extended domain, performing constraint smoothing, abandoning an external block, and retaining node coordinate information in the target domain; and exporting the reserved node coordinate information, the current volume fraction and the geometric structure to obtain the fragmentation and expansion structure.

Content relevance based table query answering is described. In one or more examples, a query and a table are received. The table includes a plurality of cells. A plurality of scores for calculated that correspond to the plurality of cells based on the query. One or more machine-learning models are then leveraged to generate a search result from the query, table, and scores, which is presented in a user interface for display.

Provided herein are compositions and methods for identifying the cell type origin of cells based on RNA sequencing (RNA-seq) data.The method provided herein may include: receiving a plurality of sequencing read counts; providing a set of detected cell types and a related gene set G for each cell type, such that each gene set G comprises a plurality of genes g; scoring the sequencing read counts to generate an assignment score; and assigning each cell among the plurality of cells to the cell type with the highest assignment score, thereby identifying the cell type origin of each cell.This method can be implemented, for example, using a computer system.

The application discloses a kind of artificial cells for single-cell mass spectrometry and preparation method thereof, wherein artificial cell includes internal water phase, intermediate oil phase and external water phase;Internal water phase includes polyethylene glycol and polyvinyl alcohol aqueous solution, intermediate oil phase includes L-alpha-phosphatidylcholine chloroform and hexane mixture;External water phase includes PVA and F-68 aqueous solution.Compared with natural cell sample, the novel artificial single cell based on microfluidic self-assembly developed in the application has better uniformity, stability and controllability, effectively avoids significant measurement difference between single-cell individual samples, and effectively solves the problem of difficult stable preservation of biological samples.The proposed artificial cell preparation method will largely solve the problem of lack of standard reference material in the field of single-cell mass spectrometry, making the results of single-cell mass spectrometry method more accurate, reliable and mutually recognized.

The invention relates to the technical field of biological tissue cell detection, in particular to an in-situ biological tissue cell free radical detection device and method based on EPR. The technical problems that in the prior art, a fluorescent probe is prone to being oxidized, the detection accuracy is affected, a traditional EPR method needs to freeze or fix a sample, a cell sample is prone to being inactivated, and free radicals in the sample are inactivated or attenuated are solved. According to the technical scheme, the in-situ biological tissue cell free radical detection device based on the EPR comprises a culture cabin, a central controller, a culture dish, a cleaning fluid storage rack, a control assembly, a detection assembly and a temperature control assembly; through the design of the movable sterile liquid suction head and the liquid conveying channel, automatic sampling and conveying are achieved, the problem that free radicals are inactivated or attenuated in traditional EPR detection is solved, the authenticity and reliability of a detection result are ensured, and real-time, dynamic and in-situ detection of biological free radicals is achieved through automatic operation of a central control system.

The present disclosure provides example embodiments for automatically or semi-automatically classifying cells in microscopic images of biological samples. These embodiments include methods of selecting training sets for the development of a classifier model. The disclosed selection embodiments can allow for retraining of a classifier model using training examples that have undergone the same or similar culture conditions as a target sample. These selection embodiments can reduce the human effort required to specify the training examples. The disclosed embodiments also include classifying individual cells based on metrics determined for the cells using phase contrast imaging and out-of-focus brightfield imaging. These metrics can include size, shape, texture, and intensity-based metrics. These metrics are determined based on segmentation of the underlying imagery. In some embodiments, the segmentation is based on phase contrast imaging and / or out-of-focus brightfield imaging of the biological sample.

The invention relates to the technical field of pharmacy and biology, in particular to a high-content drug screening method and system based on ControlNet-PPO. The method comprises the following specific steps: according to a current cell state, adopting a PPO algorithm reinforcement learning strategy to generate a combined action instruction for controlling release of various drugs; applying drug disturbance to cells based on the combined action instruction, and obtaining a disturbed cell image; inputting the cell image as a condition into a pre-trained ControlNet, and generating an expected cell state image under the action instruction; calculating a composite reward value based on a state difference between the expected cell state image and a normal cell reference image; and updating the reinforcement learning strategy by using the composite reward value, and iteratively optimizing the drug combination action until the cell state is converged to be close to the normal state, thereby obtaining an optimal drug combination path. By adopting the method, the synergistic effect of multiple drugs can be effectively captured and utilized, and the method has the characteristic of high optimization capacity.

Provided is a subject measurement device capable of efficiently performing a subject inspection service including an inspection of malaria infection. A subject measurement device for measuring a subject collected from a subject includes: a measurement unit for preparing a measurement sample from the subject and a reagent and detecting at least an optical signal corresponding to cells in the measurement sample; and an analysis means for analyzing the cells on the basis of the measurement of the subject by the measurement means. The measurement unit is capable of selectively performing a plurality of measurement operations on a subject. The plurality of measurement operations include: a first measurement operation in which a subject is measured using a first reagent containing a first fluorescent dye for staining white blood cells for classification of white blood cells, and a second measurement operation in which the subject is measured using a second reagent containing a second fluorescent dye for staining white blood cells for classification of white blood cells; a second measurement operation in which the subject is measured using a second reagent containing a second fluorescent dye that stains cells suspected of being infected with malaria; and a third measurement operation in which the subject is measured using the first reagent and the second reagent.

The application discloses a method for detecting double allelic gene edited cells based on CRISPR / Cas12a technology. The application provides crRNA, wherein the nucleotide sequence of a target point is SEQ ID NO. 6. The crRNA is obtained by in vitro transcription of a transcription template; the transcription template is a product obtained by annealing of a single-stranded DNA molecule shown in SEQ ID NO. 10 and a single-stranded DNA molecule shown in SEQ ID NO. 13. The application provides crRNA of a CD71 gene, and a CRISPR / Cas12a system is constructed by using the crRNA, CRISPR / Cas12a detection is carried out, double allelic gene edited cells of the CD71 gene induced by CRISPR / Cas9 are screened, and the method is simple, easy, fast, and convenient for economically and effectively screening a large number of mutant cells.

A deep neural network-based method for detecting living cell morphology may include identifying and locating one or more living cells within an acquired image to be detected by using a deep neural network-based target detection model, so as to extract one or more living single cell images. segmenting the image of the one or more living single cells by using a deep neural network-based cell segmentation model, so as to obtain one or more feature part of the one or more living single cells. and analyzing and determining a morphological parameter of the one or more living single cells based on the one or more feature parts. Thus, the activity of the detected cells can be ensured, and a non-destructive, accurate, and rapid detection of living cell morphology can be achieved.

The invention relates to a lattice structure manufacturability evaluation method based on a processing path, and the method comprises the steps: generating a processing path model of lattice cells based on the parameters of the lattice cells, the processing path model comprising multiple layers of processing paths; sequentially carrying out first constraint, second constraint and / or third constraint on each processing path, and directly carrying out manufacturability evaluation on the lattice cells based on the processing paths on the premise of not depending on a geometric model; the evaluation process comprises the steps of calculating whether the cell wall thickness meets the minimum path width or not, judging whether the included angle constraint of the center connecting line of the adjacent layers of molten pools meets the suspension angle limitation or not, and checking whether the free length of the suspension part is within the allowable range or not; and finally, comprehensively evaluating the manufacturability grade of the lattice cells according to the constraint coincidence condition of each path. The manufacturability of the lattice structure can be efficiently and accurately predicted, and the method is particularly suitable for prediction and evaluation before manufacturing of a large-scale micro-lattice structure with a huge amount of fine units.

This invention provides a method for processing live single-cell extraction based on deformation trends, comprising the following steps: Step S1: Controlling a microfluidic chip to immerse itself in a culture medium containing adherent cells while maintaining a preset gap, controlling the injection flow rate of the injection channel and the aspiration flow rate of the aspiration channel to form a microjet acting on the cells; Step S2: Controlling an image processing module to receive and process cell morphology images on the culture substrate acquired by a microscopic imaging module, and calculating deformation parameters based on the comparison between the cell area in the current frame image and the initial cell area; Step S3: Comparing the deformation parameters with critical deformation parameters obtained through experimental calibration, and when the deformation parameters are greater than the critical deformation parameters, controlling a fluid drive module to reduce the injection flow rate and / or the aspiration flow rate; or, calculating a comprehensive damage risk index based on the deformation parameters, and when it is greater than 1, reducing the injection flow rate and / or the aspiration flow rate.

This disclosure provides a single-cell classification method and apparatus. The method includes: acquiring gene expression data, including the expression level of genes in each of multiple single cells; constructing a cell relationship graph among the multiple single cells based on the gene expression data, where nodes represent single cells and edges represent relationships between single cells; extracting features from the cell relationship graph using a graph convolutional neural network to obtain a feature embedding representation corresponding to the cell relationship graph; and classifying the multiple single cells using a classification network based on the feature embedding representation to obtain cell types corresponding to each single cell. Thus, by utilizing a graph convolutional neural network and a cell relationship graph that displays higher-order relationships among multiple single cells, the accuracy of single-cell classification is effectively improved.

This invention discloses a mechanical superstructure design method and a mechanical superstructure designed using this method, belonging to the field of mechanical superstructure technology. The method includes establishing a finite element model of a multistable unit cell, which comprises a support frame and multiple sets of arc-shaped beam structures, each set consisting of two intersecting arc-shaped beams; setting initial geometric parameters for each set of arc-shaped beam structures; obtaining the jump load thresholds for the arc-shaped beam structures in each direction through finite element analysis; determining whether the jump load thresholds in each direction increase or decrease sequentially according to a preset spatial direction; if not, adjusting the corresponding geometric parameters and iteratively solving until the sequence requirement is met, forming a programmable multi-axis jump sequence; outputting the optimized final geometric parameters; and constructing multiple multistable unit cells based on the final geometric parameters and assembling them into an array structure along spatial directions. This invention provides a mechanical superstructure capable of independent deformation in multiple spatial directions and with a programmable jump sequence.

The application discloses a method for predicting different metabolic states of cells in cancer and metabolic characteristic subtypes of the cells based on a metabolite-protein interaction network, and the method comprises the following steps: (1) identifying the classification and metabolic state of the cells: preprocessing data, filtering low-quality cells; performing twice principal component analysis according to key genes; performing twice dimension reduction clustering on the cells respectively; (2) predicting metabolic characteristic subtypes of a queue according to the proportion of different metabolic states of cells in the sample. The method can identify the metabolic state of the cells and metabolic subtypes, and provides a new perspective for cancer research.

The invention provides an immune typing method and device, a storage medium and a program product, and the method comprises the steps: obtaining sample data, and carrying out the preprocessing of the obtained sample data; on the basis of the preprocessed sample data, the enrichment fraction of the multiple immune cells is calculated, N cells with statistical significance are screened out from the multiple immune cells to serve as alternative cells, and N is a natural number; n types of cells are selected from the N types of alternative cells through survival analysis to serve as first-choice cells, n is a natural number and is smaller than N, and the remaining (N-n) types of cells serve as second-choice cells; and circularly traversing multiple combinations of the secondarily selected cells, selecting one of the combinations through clustering analysis, and jointly using the selected combination and the preferred cells as an immune typing cell combination.

This invention relates to the field of sensor measurement technology and discloses a dual-modal sensor based on a single unit and its measurement method. The sensor includes: a flexible upper substrate for providing flexible support and encapsulation protection for the entire sensor surface; an upper electrode layer containing a first circular electrode for generating capacitance changes in response to pressure stimulation and serving as the output terminal for electrical signals; an intermediate sensitive layer; a lower electrode layer; and a flexible lower substrate. The method includes: system initialization, synchronous acquisition and transmission of dual-modal signals, signal processing, and signal output and display. This invention, through the combination of concentric circular electrode design and independent signal channels, achieves hardware decoupling of temperature and pressure signals, solving the problems of temperature drift interference in pressure measurement and reliance on algorithm compensation caused by traditional sensors sharing the same electrode and signal channel, fundamentally improving the accuracy and reliability of dual-modal measurement.

The invention provides a report page generation method and device and a readable storage medium. The report page generation method comprises the steps that a to-be-extended cell list of an initial report page and preset design state information are acquired; based on the to-be-extended table cell list and the design state information, determining a father-child grid hierarchical association relationship of each table cell in the to-be-extended table cell list and a management and control area range of the table cell and a relative child grid; constructing an extension lattice model containing a cell extension state according to a father-child lattice hierarchical association relationship and a control region range; screening table cells needing to be extended according to the extension grid model, adding the table cells into a queue, and determining an extension table model; and rendering according to the extension table model and a preset page rendering rule to obtain a target report page. Through data input, relation judgment, model construction and extension execution, a rendered page is finally output, and the design limitation of a row header, a column header and a cross point is broken through.

The present invention belongs to the field of biotechnology. In particular, the present invention relates to a method for detecting chromatin accessibility or DNA binding protein footprint in cells based on a two-enzyme method. More specifically, the present invention relates to a method for converting information on the openness of chromatin into information on mutations in DNA sequences by means of adenine methyltransferase and adenine deaminase, thereby quantitatively determining the chromatin accessibility of DNA molecules and the binding footprint of DNA binding proteins, such as transcription factors.

A method for computing regional counterfactual rules to summarize recourse options is disclosed. The method includes receiving model data via an input, the model data including information that relates to a target model and a corresponding data set; training a surrogate model for the target model based on the model data; identifying, by using the surrogate model, rules for an output of the target model based on a predetermined threshold, the rules including a counterfactual rule; enumerating, by using the surrogate model, boundaries for the identified rules to partition an input space into a grid with cells, each of the cells including a hyperrectangular cell; labeling, by using the surrogate model, each of the cells with one of the identified rules based on predetermined optimality criteria; and merging, by using the surrogate model, each of the labeled cells based on a matching of the rules to generate regions of optimality.

The invention provides a method for dynamically identifying global influence factors of performance degradation of a proton exchange membrane electrolytic cell based on digital twinning, which comprises the following steps of: firstly, respectively analyzing degradation mechanisms of components such as a proton exchange membrane, a catalyst layer and a bipolar plate; secondly, constructing an electrochemical field model, a temperature field model, a proton conduction field model, a concentration field model and a gas-liquid two-phase flow field model, and determining a coupling relationship among the five physical field models; then, based on the mechanism model and the physical field model, constructing a digital twin system, and performing online simulation according to real-time working condition input; and finally, setting a plurality of cases, and simulating the performance degradation of the proton exchange membrane electrolytic cell under the action of different global influence factors. According to the method, the influence mechanism of global factors on PEMEC performance degradation can be recognized in real time, simulation calculation of the degradation process is achieved, and accurate decision support is provided for design optimization, operation maintenance and service life evaluation of the electrolytic battery.

Embodiments of the present application disclose a path planning method, device and equipment and a storage medium. The method comprises: obtaining a sub-target graph corresponding to an environment grid map; wherein the sub-target graph comprises a sub-target set and an edge set connecting each sub-target; updating the sub-target graph according to a starting cell and / or an ending cell to obtain an updated sub-target graph; determining an initial path based on the updated sub-target graph; wherein the initial path is composed of a plurality of sub-targets in the updated sub-target graph; determining a sub-path between two adjacent sub-targets in the initial path to obtain a target path. The path planning method provided by the embodiments of the present application can improve the efficiency and accuracy of path planning by determining the path between the starting cell and the ending cell based on the updated sub-target graph.

Provided is a method (100) to generate a 3-dimensional segmentation of cells based on a stack of images taken at different focal planes within a specimen. The method comprises receiving a 2-dimensional vertical gradient map and a 2-dimensional horizontal gradient map for every focal plane (110) and determining a 2-dimensional cell segmentation map (120) for every focal plane based on the vertical gradient map and the horizontal gradient map of the focal plane. The method further comprises merging 2-dimensional cell segmentation maps of neighboring focal planes (130) to generate the 3-dimensional segmentation of the cells.

The present invention relates to isolated nucleic acid molecules, comprising a functional mammalian EGR-1 (early growth response protein 1) promoter region that is operatively linked to a gene encoding a fluorescent protein and controls expression of said gene. The present invention further relates to nucleic acid vectors, comprising said nucleic, cells comprising said nucleic acids or vectors, being capable of sensing and indicating fluid shear stress acting on themselves, and methods of generating the same. Furthermore, the present invention relates to methods of evaluating fluid shear stress acting on cells in real-time during the operation of a biotechnological device or system, methods of evaluating a biotechnological device or system with respect to fluid shear stress acting on cells caused by operation of said device or system, and methods of designing a biotechnological device or system, said methods using said cells.

The invention provides a data processing method, a data processing device and related equipment, which are used for reducing the operation complexity of a form obtained by screening a multi-dimensional database. The method comprises the steps that a first request is obtained, the first request carries a first formula, and the first request is used for generating data of formula cells based on the first formula and a target form associated with the first formula; the target form is a form obtained by screening data in a multi-dimensional database based on a target screening condition, and the formula cell is a cell of the first formula in the target form. The calculation script is generated according to the first formula and the pseudo coordinates of the first cells, the pseudo coordinates of the first cells are used for indicating viewpoint POV members of the first cells in the multi-dimensional database, the first cells comprise formula cells and data cells referenced by the first formula, and the first cells are cells in the target form. And running the calculation script to generate a processing result of the first request.