68 results about "Cellular resolution" patented technology

Processes to spatially align single cells to yield a specimen map with single cell resolution are provided. Methods can perform spatial omics on a specimen to yield spatial omics data. The spatial omics data can be used in combination with single cell omics data to assign single cells to spatial coordinates to yield a resolved specimen map.

The invention discloses a label-free nano plastic and single cell interaction monitoring imaging method which comprises the following steps: placing a sensing chip attached to cells on an SPRM, and recording a cell SPR image in the interaction process of the cells on the sensing chip and nano plastic; after the cell SPR image and the cell bright field image are compared to determine the corresponding area of the single cell in the SPR image, the deformation data of the cell membrane in the interaction process of the single cell and the nano plastic are obtained according to the SPR signal intensity of the area of the single cell, and the monitoring of the interaction of the nano plastic and the single cell under the resolution of the single cell is realized. The technical support is provided for researching the binding kinetics and cytotoxicity of the nano plastic.

Compositions and methods for assessing relative macromolecule abundance (for example, RNA expression levels) in a spatially-defined manner across a tissue sample (for example, from brain, lung, liver, kidney, pancreas, and / or heart) are disclosed, specifically providing deep transcriptomic coverage at high-resolution (for example, at approximate 10 μm (single cell) resolution) across multiple locations assessed across the tissue sample.

The present application relates to a kind of intercellular interaction reconstruction method and system based on graph convolution and long short-term memory attention network.The method comprises the following steps: collecting spatial transcriptome data under single cell or subcellular resolution, obtaining the gene expression matrix corresponding to each cell;Determine the spatial proximity between each cell, determine whether there is interaction between cells, thereby constructing cell graph;Using graph convolution and long short-term memory attention network combination, form feature extraction network to extract features from cell graph, obtain latent feature representation;Using inner product to decode latent feature representation, generate new adjacency matrix, obtain the intercellular interaction after reconstruction.By introducing the combination of graph convolution and long short-term memory attention network, the spatial correlation in cell graph structure can be captured while learning intercellular interaction, and the intercellular interaction is reconstructed, so that the intercellular interaction and the organization homeostasis of organism can be better understood.

Embodiments disclosed herein provide for spatially tagged nuclei that are compatible with any genomic or multiomic single cell / nuclei assay to allow generation of a spatially resolved single cell sequencing library with single cell resolution.

A spatial in situ sequencing method, belonging to the field of biology, is proposed. It utilizes an electric field-assisted directed migration of mRNA and in-situ capture with primers on a microarray surface to enrich tissue and release mRNA. In-situ reverse transcription generates covalently fixed cDNA, ensuring high positional stability during multiple rounds of hybridization and imaging. After reverse transcription, tissue is digested to remove tissue, reducing spatial hindrance and background interference, while the cDNA remains at its original coordinates due to covalent anchoring. Combining coding probe hybridization and RCA, single-molecule-level signal amplification and recognition are achieved. Through decoding and single-cell segmentation, transcripts are mapped to their respective cells, constructing a single-cell resolution spatial gene expression map. This method does not rely on multi-round DAPI mapping or other endogenous morphological marker-based multi-cycle image registration methods, making it suitable for high-throughput spatial in situ sequencing and significantly improving robustness and versatility in complex imaging scenarios such as thick tissue sections and low signal-to-noise ratios. It is applicable to high spatial resolution, high-throughput spatial transcriptome research.

The present invention relates to a system (1) for in vivo full-field transmission interference cell resolution imaging of an eye (6) of an individual and to a method (100) for in vivo full-field transmission interference imaging of an eye (6) of an individual.

The present application belongs to the field of genetic engineering, and provides a method for detecting RNA and ribosome interaction in situ, and a probe combination of a padlock probe and an 18S rRNA primer probe, a decoding probe and a fluorescent probe used in the detection process. The detection method of the present application has the advantages of high signal-to-noise ratio, high throughput coding capacity, subcellular resolution, low cost, simple operation and the like, and is significantly superior to traditional translational omics research technology.

In one aspect, a method of sorting cells in a flow cytometry system is disclosed, which includes illuminating a cell with radiation having at least two optical frequencies shifted from one another by a radiofrequency to elicit fluorescent radiation from the cell, detecting the fluorescent radiation to generate temporal fluorescence data, and processing the temporal fluorescence data to arrive at a sorting decision regarding the cell without generating an image (i.e., a pixel-by-pixel image) of the cell based on the fluorescence data. In other words, while the fluorescence data can contain image data that would allow generating a pixel-by-pixel fluorescence intensity map, the method arrives at the sorting decision without generating such a map. In some cases, the sorting decision can be made with a latency less than about 100 microseconds. In some embodiments, the above method of sorting cells can have a sub-cellular resolution, e.g., the sorting decision can be based on characteristics of a component of the cell. In some embodiments in which more than two frequency-shifted optical frequencies are employed, a single radiofrequency shift is employed to separate the optical frequencies while in other such embodiments a plurality of different radiofrequency shifts are employed.

The present invention relates to a two-photon holographic optogenetic stimulation method, system, device, and medium based on wavefront correction. The method comprises: step S1, selecting a target neuron from two-photon imaging and obtaining a hologram corresponding to the three-dimensional spatial position of the target neuron; step S2, selecting a target region on the hologram requiring wavefront distortion correction for the target neuron, and performing wavefront distortion correction on the target neuron in the target region to obtain a phase map containing wavefront distortion information and position information; and step S3, optically exciting the target neuron based on the phase map containing wavefront distortion information and position information. Compared with existing technologies, the present invention achieves deep single-cell resolution excitation of more neurons with a large field of view, lower excitation power, and significantly improves the accuracy and safety of optogenetic stimulation imaging.

Embodiments disclosed herein provide spatially labeled cell nucleuses compatible with any genomic or multiple groups of single cell / nucleus assays to allow for the generation of spatially resolved single cell sequencing libraries with single cell resolution.

The present invention discloses a multi-omics chip based on spatial interleaved coding, its preparation method, and its application. Based on 3D inkjet in situ DNA synthesis technology, the present invention utilizes a spatial interleaved coding strategy to produce a high-resolution, large-scale spatial multi-omics chip. This chip then uses a spatial in situ capture strategy to perform high-throughput in situ transcriptome analysis, in situ epigenomic analysis, in situ non-coding RNA analysis, and in situ proteome analysis on tissue sections. This achieves single-cell resolution and large-scale spatial coverage while maintaining a high gene count detection rate. The chip can be used to construct three-dimensional, fully covered, precise transcriptional maps or spatiotemporal maps of organs or tissues.

Compositions and methods for assessing relative macromolecule abundance (for example, RNA expression levels) in a spatially-defined manner across a tissue sample (for example, from brain, lung, liver, kidney, pancreas, and / or heart) are disclosed, specifically providing deep transcriptomic coverage at high-resolution (for example, at approximate 10 μm (single cell) resolution) across multiple locations assessed across the tissue sample

Disclosed herein include method and systems suitable for use in detection and / or prediction of microorganisms in a sample using sequencing data. In some embodiments, the method comprises converting reference sequences and sample sequences to comma-free sample codes; and detecting the presence of microbes in the sample based on alignment of the comma-free codes. In some embodiments, the method comprises detecting and / or predicting viral presence in host cell, by identifying and analyzing signature host genes. In some embodiments, the system suitable for performing the methods disclosed herein.

The invention relates to a method to indicate the clinical outcome of a cancer patient by labelling a cancer sample with labelled molecular probes, assaying the expression of a plurality of biomolecules at the resolution of a single cell and assigning a cellular identity (CI) to each single cell in the sample based on their expression pattern; then assigning a single cell pathology (SCP) patient group according to the proportion of each CI the sample contains.The invention in other aspects relates to methods of treatment of a patient with anticancer drugs according to the patient's assignment to particular SCPs. Alternatively, this aspect may be formulated as the provision of certain drugs for treatment of cancer in patients characterized by tumours assigned to certain SCPs.

The present disclosure provides a fusion protein comprising a base-editing enzyme and a protein that binds to a fragment crystallizable region (Fc region) of an immunoglobulin (e.g., nanobody, protein A, protein G, or pAG). Methods, kits, or systems of using such fusion proteins for profiling the binding events of a transcription factor or a chromatin modeling factor to a DNA in a cell or a population of cells are also disclosed.

The invention discloses a rapid evaluation method of host caries risk based on Raman spectrum, and relates to the technical field of microbiological detection. Aiming at the problem that in the prior art, it is difficult to rapidly and quantitatively reflect the early metabolic activity of the oral flora, the method introduces a stable isotope signal through heavy water labeling to obtain single-cell Raman spectrum information of the oral flora, and evaluates the metabolic activity of the flora on the basis of a characteristic parameter C-D ratio reflecting the metabolic state of microorganisms in a Raman spectrum, so that the early metabolic activity of the oral flora can be rapidly and quantitatively reflected. Therefore, the judgment of the caries risk of the host is realized. The method comprises the steps of sample collection, flora growth and metabolism law research under different concentration heavy water labeling, and metabolic activity detection under different environmental conditions. By adopting the heavy water concentration of 40%, on the premise that flora growth is not obviously influenced, rapid characterization of metabolic activity can be realized in a short time, the resolution ratio of single cells is high, and disturbance is small. The method provides a new tool for early warning of caries and oral flora metabolism research, and has a wide application prospect.

The embodiments disclosed herein provide spatially tagged nuclei that are compatible with any genomic or multi-omic single cell / nucleus assay, enabling the generation of spatially resolved single cell sequencing libraries with single cell resolution.

The invention relates to the technical field of single-cell sequencing, and discloses a high-quality single-cell Hi-C library building method, which comprises the following steps: by utilizing a cumulative effect, carrying out cross-linking immobilization, enzyme digestion, biotinylated nucleotide filling-in and connection on population cells, sorting single cells, immediately marking different bar code combinations on each cell, mixing extracts of each cell, and carrying out high-quality single-cell Hi-C library building. After mixing, the cell population is equivalent to a small amount of cell population, enriching biotinylated DNA by using streptavidin magnetic beads, and finally establishing a library. According to the method, the library quality can be remarkably improved while the single cell resolution is maintained.

The application relates to the technical field of biological industry, and discloses an analysis method for HBV expression level and fragment distribution based on single-cell RNA-seq, constructs position information of each gene of HBV in a linear transcriptome and a circular genome, and obtains a mapping relationship of the transcriptome and the genome; compares original sequencing data obtained by scRNA-seq to an HBV transcriptome reference sequence, identifies human sequences and HBV sequences, removes the human sequences, and obtains HBV source transcriptome sequences; converts the position of the sequencing sequence on the transcriptome into a comparison position on the genome through the mapping relationship of the transcriptome and the genome; calculates the number of sequencing sequences covered on each base of the genome, draws the coverage depth of each base of the HBV genome, and obtains the expression level and fragment distribution of single-cell RNA-seq sequencing data on the HBV genome. The application fills the blank of the HBV analysis method based on single-cell resolution.

The present invention discloses an intelligent method for identifying cell - cell communication in spatial transcriptome data. The method includes: preprocessing single - cell transcriptome and spatial transcriptome data; exploring the deep connections existing in omics data by using the attention mechanism to integrate single - cell transcriptome and spatial transcriptome data; mining the local and global features of each cell through a sub - graph - based mechanism; and combining with a graph attention neural network to propose an intelligent algorithm for identifying cell - cell communication at the single - cell resolution. The present invention overcomes the limitations of single - cell transcriptome and spatial transcriptome data, solves the problem of accurate identification and analysis of cell - cell communication, helps to more comprehensively reveal the co - regulation between cells, and further deepens the understanding of complex biological processes.

The invention provides a method for screening an early stage of coronary heart disease N1 protein by using a kit, and belongs to the technical field of biomedical detection, and the method comprises the following steps: sorting mononuclear cells; performing incubation; collecting a single cell fluorescence image; performing algorithm analysis; a single cell imaging and AI quantitative strategy is adopted, target mononuclear cells are enriched through high-purity sorting, target protein is labeled with a high-affinity antibody, single cell fluorescence distribution is captured through high-resolution microscopic imaging, integral optical density is calculated through an AI algorithm, and subcellular level spatial quantification of protein expression is achieved. Biomarker detection is improved from a population mean value to a single cell resolution ratio, and the analysis capability on trace expression is remarkably improved.

This invention discloses a single-cell spatial transcriptome sequencing method based on spatial coding, belonging to the field of spatial transcriptome sequencing technology. Two microfluidic chips with mutually perpendicular channels are used to add two sets of spatial coding sequences to tissue slices. Unique spatial coding combinations are formed at the intersection of the two channels, marking the spatial location information of cells. After coding, cell nuclei are extracted from the tissue slices, and high-throughput single-cell nuclear sequencing is performed to add cellular coding to single cells. Through sequencing analysis, transcripts are mapped to spatial locations according to spatial coding, and to single cells according to cellular coding, reconstructing a single-cell spatial transcriptome atlas. This method achieves single-cell spatial coding in a simple and low-cost manner, belonging to spatial transcriptome sequencing technology with single-cell resolution.

The invention discloses a method and a system for synchronously detecting intracellular microbial colonization and host response at a single cell level, and belongs to the technical field of single cell epimics and microbiomics. Microorganism colonization information and host chromatin openness information of each single cell are synchronously extracted from single cell chromatin accessibility sequencing data, and correlation analysis is performed on the microorganism colonization information and the host chromatin openness information at the single cell level, so that a cell specificity mechanism of host-microorganism interaction is analyzed. At present, a systematic method capable of synchronously realizing microbiological detection and host chromatin accessibility analysis under single cell resolution is not reported yet, and the method fills the technical blank. The method can solve the problem that the existing sequencing technology based on 16S rRNA, 18S rRNA or scRNA-seq is difficult to analyze microorganism colonization and host chromatin accessibility synchronously and highly sensitively at the single cell level, and provides an innovative tool for revealing a host-microorganism interaction mechanism of cell specificity in complex tissues.

The invention belongs to the technical field of biology, and discloses a single-cell communication tracing system based on a cell penetrating nucleic acid tag and application thereof. The tracing system comprises a carrier containing an inducible promoter, wherein the carrier expresses CellTag-RNA (Ribonucleic Acid), fat-soluble secretory fluorescent protein and fluorescent protein fusion protein which cannot be secreted. After the system is expressed in cells, fat-soluble secretory fluorescent protein and CellTag-RNA form a compound and are transferred into adjacent receiving cells, CellTag bar codes of the receiving cells and sending cells can be detected at the same time by performing single-cell sequencing on the whole tissue, and whether the receiving cells are amplified or not can be judged according to fluorescence expression and CellTag occurrence frequency. By analyzing the sharing mode of the bar code, the development pedigree, the spatial proximity relation and the interaction network of the cells can be synchronously reconstructed with the single cell resolution, so that the dynamic structure and the functional module of the tissue are disclosed on the spatial-temporal scale.

The application discloses a kind of based on deep learning's pathological image proteomics analysis method and system, it is related to bioinformatics, the method includes: using laser microdissection and mass spectrometry constructs paired image-protein dataset;Adopt pre-training VGG16 convolutional neural network to extract image deep feature, fusion cell morphological feature constructs whole proteome regression mapping model;Through U-Net single cell recognition and iterative deconvolution algorithm output cell level protein expression matrix;Combining mixed semi-supervised learning strategy handles label scarcity problem;Based on protein expression matrix, dimension reduction clustering, spatial heterogeneity quantification (CV+SHI) and visual analysis are carried out.The application realizes the regression mapping of pathological image to whole proteome (>2800) for the first time, breaks through the flux bottleneck of traditional virtual staining, realizes true single cell resolution proteomics, and provides new means for precision medicine.

A microfluidic control chip, system, and method for single-cell extracellular vesicle isolation and analysis are disclosed. The microfluidic control chip includes a flow layer and a control layer. The flow layer includes a sample / air inlet, a waste liquid outlet, a micron-sized trapping channel containing contraction and expansion structures, a micron-sized gas flow channel, a micron-sized single-cell trapping structure, and a micron-sized single microsphere trapping structure. The control layer includes an air inlet, a micron-sized gas flow channel, and a micron-sized protrusion structure. A microfluidic control chip imaging system for single-cell extracellular vesicle isolation and analysis is also disclosed, comprising the microfluidic control chip, a micro-injection pump, a pressure controller, a capillary tube, a PFA tube, and a fluorescence microscope. The microfluidic control chip of this invention can simultaneously analyze biomarkers expressed on the surface of single cells and single-cell secretory extracellular vesicles. Correlation analysis of cancer cell drug resistance with the expression levels of biomarker proteins on the surface of cells and cell secretory extracellular vesicles is achieved at single-cell resolution.

This invention discloses a spatial multi-omics sequencing method based on cross-modal generation, comprising the following steps: acquiring H&E staining images of tissue sample slices; automatically identifying and locating regions of interest (ROIs); manually cutting the tissue sample slices based on the ROIs and transferring them to a detection chip; acquiring a multi-omics expression matrix at single-cell resolution; extracting spatial feature anchor points that match the H&E staining images and the multi-omics expression matrix; performing coordinate transformation based on the coordinate mapping relationship of the spatial feature anchor points to achieve physical spatial dimension registration; and utilizing a cross-modal prediction model to perform spatial inference and full-sample information completion on discrete detection signals through spatial expression reconstruction methods. This invention effectively integrates high-precision local physical detection with global algorithm inference, ultimately outputting high-fidelity multi-omics expression information containing the entire tissue sample, completing cross-scale completion from local targeted detection to full-sample multi-omics.

To provide a solution for quantitative measurement and monitoring of cellular mechanical forces that overcomes the shortcomings of existing technologies, requires no microscope, offers real-time, high-throughput, and low-cost capabilities, the inventors provide a cellular mechanical force detection device, comprising: a base, and a micropillar array consisting of multiple micropillars disposed on the base, capable of deformation under cellular mechanical forces. Each micropillar has a light-reflecting layer at its top or upper surface. The inventors also provide a cellular mechanical force detection system including the above-mentioned device, a detection method for detecting cellular mechanical forces using the above-mentioned device, and a method for preparing the above-mentioned device. Unlike existing technologies, the above-mentioned solution offers advantages such as high throughput and low cost, single-cell resolution, real-time monitoring, high sensitivity, and the ability to simulate the cellular microenvironment; it can also simulate the composition and morphology of the extracellular matrix, thus meeting a wider range of technical needs.