123 results about "Molecular analysis" patented technology

The invention discloses an SPR response region identification method based on image semantic segmentation and time sequence alignment, and the method comprises the following steps: collecting SPR image frame sequence data, and constructing an original image sequence; performing image preprocessing operation on the original image sequence, and outputting a standardized image sequence; constructing a time sequence window image set composed of multiple continuous frames; inputting the time sequence window image set into an improved SegFormer model, and generating a response region segmentation mask image corresponding to each frame; executing cross-frame time sequence alignment operation of the response area, and outputting time sequence consistency identification mapping of the response area; performing area statistics, intensity analysis and time positioning operation; and generating a structured response region recognition result. The spatial-temporal evolution process of the response area in the SPR image sequence can be effectively recognized, the accuracy and stability of response area recognition are improved, and the method is suitable for high-precision biological detection and real-time molecular analysis scenes.

The invention belongs to the field of corn disease prevention, relates to a novel small peptide, provides a small peptide NCRP246 and application thereof in improvement of corn southern leaf blight resistance, and provides feasibility for plant disease resistance by using non-classical peptides. A corn southern leaf blight resistance identification experiment proves that NCRP246 can significantly improve the resistance of corn to southern leaf blight, and further researches that the NCRP246 reduces oxidative damage of pathogenic bacteria infection of the southern leaf blight to the corn by reducing H2O2 accumulation so as to mediate the resistance of the corn to the southern leaf blight; the analysis from the molecular perspective proves that the NCRP246 can induce the expression of defense related genes.

The invention discloses a cross-coupling reaction site analysis system driven by a multi-modal neural network. The cross-coupling reaction site analysis system comprises a data input module, a multi-modal feature extraction module, a multi-modal neural network reasoning module, an analysis result output module and a model iterative optimization module. The system acquires molecular structure, electronic characteristics, reaction environment and historical experimental data, inputs the data into a neural network for fusion reasoning after multi-modal feature coding, and outputs reaction site recognition, activity quantification and side reaction early warning results. Through multi-modal data fusion and cross-modal feature reasoning, accurate recognition and comprehensive risk assessment of reaction sites are realized, the accuracy and reliability of complex molecule analysis are remarkably improved, the dependence on high-cost calculation and experimental trial and error is greatly reduced, and the method is suitable for large-scale popularization and application. And meanwhile, the universality and the self-adaptive optimization capability of the system in different coupling reaction systems are enhanced.

The present disclosure relates generally to biomarker discovery and patient stratification, and more specifically to machine learning techniques for discovering relevant biomarkers using data collected as part of the standard-of-care (SoC), which can be used to identify a relevant patient population for a therapeutic with a known mechanism of action (MoA). An exemplary method for predicting activity of a molecular analyte of a patient comprises: training a first module of a machine learning model based on a plurality of medical images of a first cohort; training a second module of the machine learning model based on one or more molecular analyte data sets obtained from a second cohort; receiving a medical image from the patient; and predicting, using the trained first and second modules of the machine learning model, the activity of the molecular analyte from the medical image of the patient.

A hybrid inductively coupled plasma mass spectrometer (ICP-MS) system is disclosed for simultaneous elemental and molecular analysis in positive and negative polarities. It includes an ICP torch that generates plasma with a buffer gas, producing both positively and negatively charged ions from a sample. Positioned between the sampler and skimmer, an insert with a defined geometry forms a reaction chamber. Various embodiments feature multiple apertures for pressure control, a rotatable disk for aperture regulation, a slider gate for pressure adjustment, a circular gate with adjustable radial apertures, and an inlet for introducing gases, reagents, dopants, or analytes. These components enable precise pressure modulation, optimizing performance for dual-polarity mass spectrometry. The system enhances analytical flexibility by facilitating controlled ion reactions, improving sensitivity and specificity for both elemental and molecular applications. This innovation expands ICP-MS functionality, supporting diverse scientific and industrial applications requiring high-precision mass analysis.

The invention discloses an EV membrane protein single molecule detection method based on droplet microfluidics and application thereof. The method comprises the following steps: firstly, constructing an Ab-oligo compound which is formed by sequentially connecting an antibody, Linker, Linker connection DNA, RNA capable of being specifically cut by RNA enzyme and template DNA for starting signal amplification; then capturing the extracellular vesicles in the plasma by using the CD9 / CD63 / CD81 functionalized magnetic beads; the method comprises the following steps: adding an Ab-oligo compound and a sealing buffer solution into extracellular vesicles, incubating, removing the uncombined Ab-oligo compound, adding RNA enzyme for incubating and enzyme digestion, collecting template DNA for starting signal amplification, and performing microdroplet digital PCR analysis to realize single molecule analysis of EV membrane protein. According to the invention, the one-to-one correspondence relationship between the antibody and oligonucleotide is established through Linker for the first time, single protein information is converted into single nucleic acid chain information, and EV membrane protein single molecule detection is realized. The method is simple to operate, can qualitatively and quantitatively detect the single EV membrane protein, and is beneficial to further research on the relationship between the EV membrane protein and diseases.

The invention discloses a method for high-purity sorting and capturing of rare cells. According to the method for high-purity sorting and capturing of the rare cells, the cells are spread firstly, then the positions of the target cells are searched and determined, then a probe is used for discharging a buffer solution outwards to blow away non-target cells around the target cells, and then fluid power is used for capturing the target cells without damage. Finally, the target cells can be released into a receiving container, and high-purity sorting and capturing of the rare cells are achieved. A device matched with the method is simple in structure and easy to operate, and the method has the advantages that repeated and massive dilution is not needed, the cell sample spreading speed is high, the target cell sorting purity is high, the omission rate is low, in-situ capture is achieved, and repeatability is good. The method is suitable for the fields of single cell screening and analysis, single cell culture, single cell drug screening, single molecule analysis, gene screening, sample purification, antibody screening, microbiological research and the like.

A biomolecule analysis method of the present disclosure includes: preparing a biomolecule analysis device including a thin film, a first liquid tank and a second liquid tank separated by the thin film, a first electrode disposed in the first liquid tank, and a second electrode disposed in the second liquid tank; and forming a nanopore in the thin film by applying a first voltage between the first electrode and the second electrode in a state where a nanopore forming solution is enclosed in the first liquid tank and the second liquid tank, wherein the nanopore forming solution contains ammonium ions and sulfate ions.

The present disclosure relates generally to biomarker discovery and patient stratification, and more specifically to machine learning techniques for discovering relevant biomarkers using data collected as part of the standard-of-care (SoC), which can be used to identify a relevant patient population for a therapeutic with a known mechanism of action (MoA). An exemplary method for predicting activity of a molecular analyte of a patient comprises: training a first module of a machine learning model based on a plurality of medical images of a first cohort; training a second module of the machine learning model based on one or more molecular analyte data sets obtained from a second cohort; receiving a medical image from the patient; and predicting, using the trained first and second modules of the machine learning model, the activity of the molecular analyte from the medical image of the patient.

The present disclosure relates generally to biomarker discovery and patient stratification, and more specifically to machine learning techniques for discovering relevant biomarkers using data collected as part of the standard-of-care (SoC), which can be used to identify a relevant patient population for a therapeutic with a known mechanism of action (MoA). An exemplary method for predicting activity of a molecular analyte of a patient comprises: training a first module of a machine learning model based on a plurality of medical images of a first cohort; training a second module of the machine learning model based on one or more molecular analyte data sets obtained from a second cohort; receiving a medical image from the patient; and predicting, using the trained first and second modules of the machine learning model, the activity of the molecular analyte from the medical image of the patient.

The invention relates to the technical field of signal decoding, in particular to a single-molecule signal decoding method based on an artificial intelligence algorithm, which specifically comprises the following steps: performing baseline correction on an original current signal sequence to obtain a corrected current signal dynamic baseline sequence; conducting conductance fluctuation component separation through power spectrum density and frequency band division to obtain a main current signal of the molecular event; dividing into independent molecular event segments, and extracting stable features to obtain a complete local segment stable feature set; splicing and correcting to obtain a corrected complete single molecule track; and performing similarity contrastive analysis with a standard control single-molecule trajectory to obtain an optimized single-molecule trajectory. According to the method, the problem that in the prior art, the application range and precision of the technology in complex biomolecule analysis are limited due to the fact that a single-molecule signal is difficult to be accurately matched with a standard control track in a high-salt environment is solved.

Methods of detection and identification of microbial eye infections by molecular analysis of nucleic acid in tear samples are provided. 16S rDNA is amplified by PCR directly from tear samples without extracting DNA and the amplification products are sequenced by nanopore sequencing so that the microbes can be identified.

The present disclosure relates to methods and kits for analyzing a macromolecule. In some embodiments, the present disclosure relates to macromolecule analysis methods which employ barcoding and nucleic acid encoding of molecular recognition events. Also provided herein is a method and related kits for transferring information using a plurality of enzymes, including for performing a ligation, extension, and cleavage reaction with nucleic acid molecules associated with the macromolecule for analysis. In some embodiments, the macromolecule for analysis comprises a peptide, a polypeptide, or a protein.

A method for detecting a target of interest in a tissue sample is disclosed. The method includes: a) obtaining or having obtained a tissue sample, the tissue sample comprising DNA, non-RNA molecules, and RNA, the RNA comprising the target of interest; b) permeabilizing the tissue sample; c) substantially degrading DNA in the tissue sample; d) introducing primers or probes specific for the target of interest into the tissue sample, wherein the primers or probes bind to the target of interest; and e) detecting the target of interest in the tissue sample by detecting the primers or probes bound to the target of interest. A method for producing a hydrogel within the tissue sample is also disclosed.

Provided herein are methods, compositions, systems and kits to amplify DNA, RNA and protein macromolecules. In particular, provided herein are compositions and methods to amplify macromolecules for molecular analysis including low abundance template, single-cell and single nucleus applications.

Every year, approximately 94 million cases of Salmonella gastroenteritis, with 155000 deaths, are reported each year and 85% of them reported to be food-borne. Investigation of the foods whether they are clean for Salmonella and sensitivity, easy applicability, absence of false positivity and negativity and the speed are the features sought in the analysis method for this investigation. It is not desirable for analysis to detect the presence of dead bacteria in food. Although the final product does not contain microbiologically harmful live bacteria during the food process, the detection of dead bacteria transmitted before the process causes the food product to be unfairly diagnosed as harmful. To prevent this situation, the analysis kits depending on molecular methods, increase their microorganism detection levels up to to 104 while reducing their sensitivity. Since the molecular methods cannot discriminate dead and live organisms, a confirmation test is required to prove that the positive result of the analysis belongs to the live bacteria in the food, which results in additional cost and time loss. In the same way, it is necessary to verify whether the colonies that grow in the gold standard culture method, belong to Salmonella bacteria. In the developed system; 105 dead bacterial DNA is eliminated in the food to prevent false positive results and the minimum detection limit is 10 bacteria. Also, in developed system, 4 primers specific to 6 regions of DNA are used. Therefore, the specificity of the method is very high (99.9%) and no verification test is needed. Since PCR systems require a device with complex temperature control units, they can make analysis in a laboratory-dependent manner. In the proposed system, DNA is amplified at constant temperature; no temperature cycle is required, therefore no complex instrument and laboratory infrastructure are required. All the procedures can be easily performed outside the laboratory on a portable mini-heater where pre-enrichment, DNA isolation from the sample and PCR steps are performed. For molecular analyses, the device is required to display the result of imaging or analysis. In the developed method, DNAs amplified by the loop-mediated isothermal DNA amplification method, are hybridized and combined with the labeled probe and then can be read by lateral flow method with the naked eye. As the results are visible by eye, no additional device is required. The classical culture method is accepted as the gold standard, but the duration of analysis is 7 days for positive samples, 3 days with verification test, for the molecular methods, and 5.5 hours including pre-enrichment time in the developed system.

To provide use of molecular profiling for deriving recommendation of individualized treatment for a patient.SOLUTION: Comprehensive molecular profiling provides a wealth of data concerning the molecular status of patient samples. Such data can be compared to patient response to treatments to identify biomarker signatures that predict response or non-response to such treatments. This approach has been applied to identify biomarker signatures that correlate with response of cancer patients to platinum-based chemotherapy. Described herein are data structures, data processing, and machine learning models to predict a probability of benefit of a treatment for a disease or disorder of a subject having a particular set of biomarkers, as well as an exemplary application of such a model to precision medicine, e.g., to methods for selecting a treatment based on a molecular profile, e.g., a treatment comprising platinum therapy.SELECTED DRAWING: Figure 1C

The invention relates to a process for analysing single molecules, in particular for sequencing of single nucleic acid molecules.

Provided herein are methods and compositions for rapid, highly sensitive detection of molecular analytes such as antibodies, proteins, and small molecules using protein-driven nucleic acid assemblies to activate CRISPR-Cas nucleases. Also provided herein are uses of the sensitive analyte detection methods in an analyte detection platform and in convenient low-cost diagnostic assays such as lateral flow devices for point-of-care use.

The invention relates to a process and a device for analyzing single molecules, particularly to the parallel analysis of a plurality of single molecules. It is suitable for detecting interactions, e.g. binding between single molecules and / or reactions, e.g. elongation or degradation of single molecules. Particularly, the process of the invention relates to the sequencing of single nucleic acid molecules. The single molecule to be analyzed is present in free form, i.e. dissolved or suspended in a liquid medium, within a reaction space formed around the sample spot. According to the present invention, an electrical field is applied across the reaction space, whereby a concentration of single molecules, at the sample spots is effected.

Provided herein are methods and systems for high throughput sequencing of nucleic acids for the surveillance of pathogens in a population and efficient identification of new pathogen variants of concern.

The invention relates to the field of gas analysis and analysis of volatile organic substances, is intended for the generation of ions with soft ionization and can be used as an ion source in gas chromatographs (GC) with a mass spectrometric detector and other analytical instruments. A mass spectrometer with the said ion source and a method of ionization using the mass spectrometer are also described. The technical result consists in simplifying the design, reducing the mass and dimensions of the mass spectrometer and the ion source, ensuring controlled fragmentation of molecules, including eliminating unwanted fragmentation of molecules during the ionization process, increasing the sensitivity of the analysis of molecules with the subsequent possibility of easier decoding of mass spectral information, simplification installation and use of the ion source without changing the design of the mass spectrometer, providing a higher signal-to-noise ratio.

This invention discloses a method for SPR response region identification based on image semantic segmentation and temporal alignment, comprising the following steps: acquiring SPR image frame sequence data to construct an original image sequence; performing image preprocessing operations on the original image sequence to output a standardized image sequence; constructing a temporal window image set composed of multiple consecutive frames; inputting the temporal window image set into an improved SegFormer model to generate a response region segmentation mask map corresponding to each frame; performing cross-frame temporal alignment operations on the response regions to output a temporal consistency identifier mapping of the response regions; performing area statistics, intensity analysis, and temporal localization operations; and generating a structured response region identification result. This invention can effectively identify the spatiotemporal evolution process of response regions in SPR image sequences, improving the accuracy and stability of response region identification, and is suitable for high-precision biological detection and real-time molecular analysis scenarios.

The application discloses a test paper for detecting diethylstilbestrol and a preparation method thereof, and belongs to the technical field of small molecule analysis and detection. The test paper for detecting diethylstilbestrol comprises two parts of a test paper main body and a photothermal signal probe. The test paper main body comprises, in a horizontal direction, a sample pad, a nitrocellulose membrane (NC membrane) and an absorption pad which are sequentially and overlappedly pasted on a PVC base plate from top to bottom. The NC membrane comprises a detection zone (T zone) and a quality control zone (C zone). The T zone is fixed with diethylstilbestrol-BSA, and the C zone is fixed with a secondary antibody. The photothermal signal probe is a Bi2MoO6@NiS-mAb mixed solution. When the test paper is used for detecting diethylstilbestrol, the detection mode is flexible, the linear range is wide, the sensitivity is high, and the specificity is good.

The invention discloses a methylation marker combination for detecting gastric cancer, a corresponding primer probe combination, a kit and application thereof. The methylation marker combination related to the gastric cancer comprises a CpG methylation site cg08630279 of a ZNF569 gene, a CpG methylation site cg24773720 of a GHR gene and a CpG methylation site cg20622089 of a CNR1 gene, wherein the CpG methylation site cg08630279 of the ZNF569 gene, the CpG methylation site cg24773720 of the GHR gene and the CpG methylation site The methylation levels of the ZNF569, GHR and CNR1 sites are related to gastric cancer staging, and the ZNF569, GHR and CNR1 sites can be used as high-specificity markers for early screening of gastric cancer. A primer probe combination for detecting the marker combination comprises specific upstream primers, downstream primers and probes aiming at methylation sites of all markers. The kit comprises a primer probe combination, and also comprises a positive control, a negative control and a quality control reagent. Three-site combined detection is adopted, the detection sensitivity in a gastric cancer blood sample reaches 91% or above, the specificity reaches up to 100%, the kit is used for auxiliary screening, detection or molecular analysis related to gastric cancer and precancerous lesions of the gastric cancer, and a technical scheme high in sensitivity, high in specificity and good in repeatability is provided for clinical detection.

The invention belongs to the technical field of gene mining, and particularly relates to a multi-level evidence and artificial intelligence character key gene mining method and system, and the method comprises the steps: S1, constructing a multi-omics database and integrating an interaction network; s2, predicting by using different machine learning algorithms; s3, constructing and applying an online platform: developing the online platform based on an integration result, and integrating a part of known interaction relationship databases; and systematically analyzing a genetic network of plant height, grains and drought resistance characters, and mining key genes. According to the method, the interaction network and multi-omics data are integrated, the mutual relation between functional genes is enriched, and all related genes of target characters are mined. And meanwhile, quantitative integration is performed on the relationship of the genes by utilizing artificial intelligence, and the importance of the related genes can be ranked. By means of the method, all related genes of the target character can be found out, key genes can be verified preferentially according to importance, and the method has important guiding significance on target character inheritance and molecular analysis.

The methods and systems described herein relate to analyzing a biological sample from a pregnant individual using long free DNA fragments. Deoxyribonucleic acid (DNA) fragments of biological samples are often analyzed using methylated CpG sites and the status of single nucleotide polymorphisms (SNPs). The CpG site and SNP are generally spaced from the nearest CpG site or SNP by hundreds or thousands of base pairs. It is little or impossible to find two or more contiguous CpG sites or SNPs on the majority of free DNA fragments. A free DNA fragment longer than 600 bp may comprise a plurality of CpG sites and / or SNPs. The presence of multiple CpG sites and / or SNPs on a long free DNA fragment as compared to a single short free DNA fragment may allow for analysis. Long free DNA fragments may be used to identify origin tissue and / or to provide information about a fetus in a pregnant female.

The invention relates to a process for analysing single molecules, in particular for sequencing of single nucleic acid molecules.

Methods and compositions for pre-treatment of samples suspected of comprising biomolecules such as nucleic acids and proteins, particularly complex samples, to maximize yield of detectable analytes extracted from the samples, and to minimize effects of compounds that interfere with biomolecule purification processes and / or that co-purify with biomolecules and inhibit downstream processes, e.g., biomolecule assay methods.

The present invention discloses a method for high-purity sorting and capturing of rare cells. The method for high-purity sorting and capturing of rare cells in the present invention first spreads the cells, then locates and determines the position of the target cells, then uses a probe to expel the buffer outward to disperse the non-target cells around the target cells, and then uses hydrodynamic force to capture the target cells without damage. Finally, the target cells can be released into a receiving container to achieve high-purity sorting and capturing of rare cells. The device used in the method of the present invention has a simple structure and is easy to operate. The method has the advantages of not requiring repeated large-scale dilution, fast spreading speed of cell samples, high sorting purity of target cells, low omission rate, in-situ capture, and good repeatability, and is applicable to fields such as single-cell screening and analysis, single-cell culture, single-cell drug screening, single-molecule analysis, gene screening, sample purification, antibody screening, and microbial research.