96 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.

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.

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 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.

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.

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 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 relates to a cell-free transcriptional electrochemical biosensor and to the use of the same for detecting specific molecular analytes, such as specific antibodies, proteins, small molecules, nucleic acids, and derivatives thereof, in complex arrays of biological samples, such as plasma, serum, blood, saliva, sweat, and the like, wherein said biosensor is based on the activation of the transcription of a specific RNA strand, induced by recognition with the analyte. The invention further relates to a method for the detection of specific molecular analytes in complex arrays of biological samples, said method being based on the use of said cell-free transcriptional electrochemical biosensor.

The invention discloses a surface water characteristic soluble organic matter molecule and reaction identification method and device, and relates to the field of environmental monitoring, the method comprises the following steps: collecting a surface water body sample of a target area, and carrying out solid phase extraction to obtain a soluble organic matter sample; carrying out determination and mass spectrometry on the dissolved organic matter sample by adopting a Fourier transform ion cyclotron resonance mass spectrometer to obtain a dissolved organic matter molecular formula of the target area; spearman correlation analysis is carried out on the key hydrological parameters and the molecular formula of the soluble organic matter of the target area to obtain characteristic soluble organic matter molecules under the influence of the key hydrological parameters; and analyzing the chemical reaction between the characteristic dissolvable organic matter molecules to obtain the chemical reaction path of the characteristic dissolvable organic matter molecules under the influence of the key hydrological parameters. According to the method, quantitative analysis of the molecular formula and the reaction path of the characteristic soluble organic matter is realized, and the influence of the key hydrological parameters on the specific soluble organic matter molecules and the chemical reaction can be identified.

The present invention relates to a novel microRNA for in vitro early diagnosis of mild cognitive impairment and Alzheimer's dementia, and a convergence diagnostic cartridge and diagnostic device using same. The novel miRNA of SEQ ID NO: 1 obtained by molecular analysis exhibits differences in expression levels in the plasma of a normal group, a mild cognitive impairment patient group, and an Alzheimer's dementia patient group, and has the effect of reducing the expression levels of mild cognitive impairment- and Alzheimer's dementia-related proteins. Therefore, by using a novel miRNA present in plasma as a molecular diagnostic index in a non-invasive manner, the present invention enables not only early diagnosis of Alzheimer's dementia but also screening for mild cognitive impairment and Alzheimer's dementia.

Disclosed herein are compositions, sensors, and kits for a carboxymethyl dextran (CMD) based linker for label-free molecular analysis. Further disclosed are methods for synthesizing a CMD-based linker for label-free molecular analysis and method for using reagent kits to immobilize a ligand on a sensor including a CMD-based linker for label-free molecular analysis.

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

A computer-implemented method and system includes accessing neurophysiological and neurovascular data recorded during sleep. A function mapping is executed from said neurophysiological and neurovascular data to a target that is one of a glymphatic flow marker, a molecular analysis marker of neurodegeneration, or a neuroimaging marker of neurodegeneration. A target prediction model is output based on the function mapping. The target prediction model can receive new neurophysiological and neurovascular data and output a predicted marker of neurodegeneration.

Disclosed is a method for whole genome amplification and analysis of multiple target molecules in a biological sample containing genomic DNA and target molecules, the method comprising the steps of: contacting the biological sample with at least one binder for at least one of the target molecules, the binder being conjugated to a tagged oligonucleotide comprising a binder barcode sequence (BAB) and a unique molecular identifier sequence (UMI); obtaining a labeled biological sample by performing a separation step to selectively remove unbound binders; simultaneously performing whole genome amplification and amplification of the tagged oligonucleotides on the labeled biological sample; creating a massively parallel sequencing library from the amplified tagged oligonucleotides; sequencing the massively parallel sequencing library; searching for the sequences of the BAB and UMI from each sequencing read; and counting the number of different UMIs for each binder.

This invention belongs to the field of organic probe molecular analysis and detection technology, and discloses a fluorescence / electrochemical dual-mode probe for detecting copper ions (Cu2+), its preparation method, and its application. The probe's molecular structure is as follows: Under argon protection and an ice-salt bath, halogenated hydroxyl chloride and pyridinecarboxyl chloride hydrochloride undergo an esterification reaction in anhydrous dichloromethane solvent catalyzed by triethylamine. The target product is obtained after extraction, drying, vacuum concentration, and column chromatography purification. This probe combines "on-screen" fluorescence detection with ratiometric electrochemical detection, enabling highly sensitive and selective quantitative analysis of free Cu2+ in complex biological samples such as dialysis fluid from Alzheimer's disease (AD) model mice. Compared to existing detection technologies, this probe has advantages such as high selectivity, low detection limit, good stability, and accurate dual-signal cross-validation results, providing a reliable tool for the accurate detection of Cu2+ in biological samples.