307 results about "Bioanalysis" patented technology

A federated distributed computational system enables secure biological data analysis and genomic medicine with enhanced oncological therapy capabilities. The system implements patient-specific tumor-on-a-chip analysis through microfluidic control systems and cellular heterogeneity preservation, while integrating fluorescence-enhanced diagnostics using CRISPR-LNP targeting and robotic surgical navigation. The architecture coordinates spatiotemporal analysis of gene therapy delivery through molecular imaging and immune response tracking, and implements bridge RNA integration with multi-target synchronization. Treatment selection is optimized through multi-criteria scoring and patient-specific simulation modeling. Each federated node contains a local processing unit for biological data analysis, privacy preservation protocols, and a hierarchical knowledge graph structure. The system implements cross-species genetic analysis, environmental response modeling, and multi-scale tensor-based data integration, enabling research institutions to collaborate on complex, large-scale biological analyses while maintaining strict data privacy controls.

A federated distributed computational system enables secure collaboration across multiple institutions for biological data analysis. The system consists of interconnected computational nodes managed by a centralized or decentralized federation manager, depending on the deployment model. Each node contains specialized components that work together to process biological data while preserving privacy. These components include a local computational engine that handles data processing, a privacy preservation module that protects sensitive information, a knowledge integration component that manages biological data relationships by connecting various data sources, and a communication interface that enables secure information exchange between nodes. The federation manager coordinates all computational activities across the network while ensuring data privacy is maintained throughout the process. This architecture allows research institutions to collaborate on complex biological analysis tasks without compromising their sensitive data, enabling breakthrough discoveries through shared computational resources and expertise while maintaining the security, compliance, and confidentiality required in biological research.

A federated distributed computational system enables secure, privacy-preserving biological data analysis and engineering through interconnected nodes coordinated in a distributed graph architecture. A federation manager allocates resources, manages data flow and lineage, establishes privacy boundaries, and maintains cross-institutional knowledge relationships. Each node contains a processing unit for biological data analysis, privacy preservation protocols for secure multi-party computation, a knowledge graph structure with supporting data stores, and encrypted network connections. The federation manager enforces all computation and data exchange through secure channels while maintaining privacy, security, and contractual boundaries. This architecture enables research institutions to collaborate on complex biological analyses without compromising sensitive data, facilitating breakthrough discoveries through shared computational resources while maintaining strict data privacy and security controls.

A federated distributed computational system enables secure, multi-institutional biological data analysis and genomic medicine through interconnected, decentralized nodes in a federated distributed graph architecture. A federation manager coordinates computational resource allocation, control and data flows, establishes privacy and security boundaries, implements multi-scale spatiotemporal analysis and simulation modeling, models cross-species or intrapopulation elements, and maintains cross-institutional knowledge relationships. Each node includes a local processing unit for biological data analysis, including multiomics and gene editing, privacy-preserving protocols for secure multi-party computation, a hierarchical knowledge graph for managing multi-domain biological relationships across spatial and temporal scales, and encrypted network connections. The system implements cross-species genetic analysis via phylogenetic integration, environmental response modeling through spatiotemporal tracking, and multi-scale tensor-based data integration with adaptive dimensionality control. This architecture enables research institutions to collaborate on complex biological analyses and genomic medicine applications while maintaining strict data privacy and security controls.

Provided herein are methods of determining a location of a biological analyte in a biological sample.

This disclosure provides methods for spatial profiling of biological analytes present in a biological sample. Methods include generating feature arrays using a master / copy format using recessed arrays, and methods for using such arrays. For example spatially-tagged analyte capture analytes can be used in spatial detection in methods to determine the location of analytes (e.g., proteins) in biological samples.

This disclosure relates to methods for spatial profiling of analytes present in a biological sample. Also provided are methods for using spatially barcoded substrates to detect a biological analyte in a cell culture, an organism, and organoid. Also provided are methods for using spatially barcoded substrates to detect the temporal profile of a biological analyte.

A federated distributed computational system enables secure collaboration across institutions for unified biological and multiomics data analysis. It comprises interconnected computational nodes managed by a central federation manager. Each node includes specialized components: a local computational engine for biological data processing, a privacy-preservation system, a knowledge integration component leveraging dynamic knowledge graphs, and a secure communication interface. The federation manager coordinates computational activities while ensuring security, privacy, legality, and contractual adherence. This architecture allows institutions, citizen scientists, and patients to collaborate on complex biological analyses without compromising sensitive data. By enabling shared computational resources and expertise, the system facilitates breakthrough discoveries while maintaining confidentiality. Additionally, it supports pro-rata or contractually defined participation in resultant benefits or knowledge, ensuring equitable collaboration.

This disclosure provides methods for spatial profiling of biological analytes present in a biological sample. Methods include generating feature arrays using a master / copy format using recessed arrays, and methods for using such arrays. For example spatially-tagged analyte capture analytes can be used in spatial detection in methods to determine the location of analytes (e.g., proteins) in biological samples.

A ginseng year identification method relates to the technical field of traditional Chinese medicinal material identification. The problems that an existing chemical or biological analysis method needs to damage a sample and is tedious, the nondestructive testing requirement cannot be met, and the accuracy rate cannot be guaranteed when a spectrum technology is adopted for detection and identification are solved. The method comprises the following steps: step 1, carrying out spectrum scanning on ginseng samples to obtain spectrum data of the ginseng samples in different years; 2, extracting the spectral data, and establishing a spectral data set; 3, constructing a local search heuristic cross model based on a genetic algorithm according to the spectral data set; and 4, performing ginseng year identification according to the local search heuristic cross model. According to the method, the limitation in the traditional method is overcome, higher identification precision and stronger analysis capability are brought, and the method is applied to the field of ginseng year identification.

A method for separating an exosome from a heterologous expression cell or a primary culture cell, and a use of an exosome in biological analysis, relating to the technical field of biomedicine. The method for separating the exosome from the heterologous expression cell or the primary culture cell of the present invention comprises: carrying out differential centrifugation on a solution to be extracted that contains an exosome, then taking out a first supernatant, carrying out high-speed centrifugation again, respectively adding iodixanol into an obtained second supernatant and a precipitate, and carrying out spontaneous density gradient centrifugation to obtain a separated purified exosome. According to the present invention, an iodixanol spontaneous density gradient centrifugation method is innovatively used to successfully carry out separation and purification to obtain the exosome having high purity and high yield, and the separated exosome is used as an experimental development universal platform for researching a membrane protein structure and functional characteristics in an original ecological cell membrane environment, and is used for biological analysis, drug screening, and disease diagnosis and treatment.

The invention relates to the technical field of biological analysis and detection, in particular to a method for accurately quantifying miRNA copy number in extracellular vesicles, which comprises the following steps: providing a DNA tetrahedron probe which comprises a DNA tetrahedron and a molecular beacon connected with the DNA tetrahedron; the molecular beacon can be specifically combined with a target miRNA and can release a detectable signal; co-incubating the extracellular vesicles and the DNA tetrahedron probe, and detecting the signal intensity of the co-incubated extracellular vesicles; and then calculating the copy number of the target miRNA in the extracellular vesicle according to the signal intensity. The method provided by the invention can realize quantitative analysis of miRNA in single extracellular vesicles, and has the advantages of avoiding damage to vesicle structures, being simple and convenient in detection steps and the like.

The invention relates to the technical field of bioanalytical chemistry, in particular to a method for simultaneously enriching and separating glycopeptides and phosphopeptides by using a bionic hydrophilic adsorbent, which specifically comprises the following steps: step 1, preparing a polyether-ether-ketone (PEEK) framework by using a fused deposition modeling method (FDM); 2, soaking the obtained PEEK framework in an aqueous solution containing dopamine hydrochloride and tris (hydroxymethyl) aminomethane, and carrying out a reaction; step 3, then, adding a mixed solution containing hyaluronic acid methacrylate, vinyl phosphoric acid, N, N-dimethyl bisacrylamide and phenyl-2, 4, 6-trimethylbenzoyl lithium phosphate into the PEEK framework; in the invention, in the aspect of material preparation, a fused deposition modeling method (FDM) is adopted to prepare a polyether-ether-ketone (PEEK) frame, and the material has good mechanical properties and chemical stability and can bear a series of subsequent complex treatment processes without being damaged.

The invention provides a miniature organism in-situ sorting device and method for deep sea, equipment and a medium. The device comprises a dry cabin module, a wet cabin module, a transition block module and a pressure buffer, the dry cabin module is used for detecting, collecting, analyzing, processing and controlling optical signals; the wet cabin module is used for collecting seawater samples, focusing sound waves and standing waves and sorting target microorganisms; the transition block module is used for transmitting electric signals and optical signals of the dry cabin and the wet cabin; the pressure buffer is used for compensating the pressure in the wet cabin, so that the pressure in the wet cabin is equal to the in-situ pressure of the deep sea. The problems that in-situ microbiological analysis and sorting are difficult to carry out due to the severe deep sea environment and the in-situ analysis and sorting flux is low can be solved; based on the structural design that the dry cabin and the wet cabin are separated and the wet cabin pressure compensation technology, the sorting device is suitable for a deep-sea in-situ high hydrostatic pressure environment, and based on the design of a flow control cell sorting chip of an acoustic wave electrophoresis or acoustic wave standing wave method, in-situ high-throughput analysis and sorting of deep-sea microorganisms are effectively achieved.

The present invention relates to methods, devices and systems for associating consumable data with analytical consumables used in biological analysis. An analysis system and related consumables are provided, wherein the analysis system adjusts one or more steps of an analysis protocol based on consumable data specifically for the consumables. Various types of consumable data are described, as well as methods for implementing analysis using the data by an analysis system. The present invention also relates to consumables (e.g., test kits and reagent containers), software, data deployment packages, computer-readable media, loading carts, instruments, systems and methods for performing automated biological analysis.

Mean corpuscular parameter values for a sample, such as a mean corpuscular hemoglobin or mean corpuscular volume for the red blood cells in a sample, can be calculated based on individual cell corpuscular parameter values for the red blood cells in the sample. These values may be obtained using a machine learning algorithm. Such a machine learning algorithm may be trained using sets of training images annotated with transducer derived mean corpuscular parameter values, thereby allowing a flow imaging based analyzer to provide parameter values which may otherwise not be available with that type of analysis tool.

The invention belongs to the technical field of biological analysis and evaluation, and particularly relates to a stem cell differentiation process multi-modal image fusion and intelligent evaluation method, which comprises a stem cell differentiation process multi-modal image fusion method: on the basis of constructing a multi-modal near-physiological mechanics microenvironment, carrying out image analysis by adopting the multi-modal image fusion method; an intelligent evaluation method for the stem cell differentiation process: developing an intelligent evaluation method based on deep learning driving on the basis of constructing a multi-modal near-physiological mechanical microenvironment, and revealing a mechanical-epigenetic regulation mechanism; the synergistic application of the two solves the core observation and regulation problems in stem cell differentiation research, and provides an industrialized intelligent platform for regenerative medicine. According to the method, the data integrity can be improved, the resolution limitation is broken through, the experiment process is accelerated, accurate mechanism analysis can be realized, automatic decision making is promoted, and the research and development cost is reduced.

The invention belongs to the technical field of biological analysis, and particularly relates to a co-extraction method for mRNA and protein in a trace sample and application. The co-extraction method mainly comprises the following steps: capturing messenger RNA by adopting Oligo dT magnetic beads so as to separate the messenger RNA from protein, and then selecting a proteome pretreatment working process based on SP3 magnetic beads. According to the technology, Oligo dT magnetic beads are innovatively selected to separate messenger RNA. The surface of the Oligo dT magnetic bead is modified with an Oligo dT sequence, so that the Oligo dT magnetic bead can selectively capture mRNA. The mRNA separation and purification technology has the characteristics of high efficiency, high purity and simplicity and convenience in operation. The problems that mRNA and protein in a trace sample are difficult to separate, the RNA amount is small, follow-up analysis cannot be met, and the proteomics pretreatment process is low in efficiency can be solved.

The invention relates to the technical field of environmental and biological analysis and detection, in particular to a method for extracting perfluorinated / polyfluorinated compounds based on confinement fluid. The method comprises the following steps: providing a multi-dimensional reticular nanopore material; growing mutually staggered carbon nanofibers on the surface of a substrate through a chemical vapor deposition method; loading a confinement fluid in a pore channel of the multi-dimensional reticular nano-pore channel material; contacting the material with a to-be-detected sample, and extracting; desorbing the extracted material by using a desorption solvent to obtain a desorption solution; and detecting the perfluorinated / polyfluorinated compounds in the desorption solution. A multi-dimensional net-shaped nano pore channel formed by mutual staggering of the carbon nanofibers provides a stable multi-dimensional micro-nano confinement space for confinement fluid. According to the structure, mass transfer and distribution of a target analyte from a complex matrix to a confinement fluid are greatly promoted, so that efficient enrichment of various perfluoro / polyfluoro compounds is realized, and the recovery rate and the detection sensitivity of the method are improved.

Embodiments described herein may be useful in the detection of analytes. The systems and methods may allow for a relatively simple and rapid way for detecting analytes such as chemical and / or biological analytes and may be useful in numerous applications including sensing, food manufacturing, medical diagnostics, performance materials, dynamic lenses, water monitoring, environmental monitoring, detection of proteins, detection of DNA, among other applications. For example, the systems and methods described herein may be used for determining the presence of a contaminant such as bacteria (e.g., detecting pathogenic bacteria in food and water samples which helps to prevent widespread infection, illness, and even death). Advantageously, the systems and methods described herein may not have the drawbacks in current detection technologies including, for example, relatively high costs, long enrichment steps and analysis times, and / or the need for extensive user training. Another advantageous feature provided by the systems and methods described herein includes fabrication in a relatively large scale. In some embodiments, the systems and methods may be used in conjunction with a detector including handheld detectors incorporated with, for example, smartphones (e.g., for the on-site detection of analytes such as pathogenic bacteria).

A microneedle device comprises a device structure, insertable to a living body and being formed with an opened niche at least partially surrounded by walls of micrometric heights above a base of the niche for allowing the niche to be filled with a blood sample upon the insertion. The device also comprises a biosensor configured to sense a bioanalyte in the blood sample and having a sensing element formed on the base. The thickness of the sensing element is less than the micrometric heights of the walls.

The invention belongs to the technical field of biological analysis and detection, and particularly relates to a photoelectrochemical-colorimetric dual-mode biosensor and application thereof in miRNA detection. According to the biosensor prepared by the invention, the bifunctional CuO-Cu2O nanoflower and the three-dimensional network g-C3N4 / AuNPs electrode are integrated, and an enzyme-assisted strand displacement signal amplification mechanism is combined, so that dual-mode collaborative detection of a target miRNA-21 is realized: in a photoelectrochemical mode, the detection limit reaches 0.35 fM (the linear range is 1 fM to 10 fM), and response is performed based on photocurrent polarity reversal; the colorimetric mode is as follows: the detection limit is 3.9 fM (the linear range is 10 fM to 10 nM), and TMB (Tetramethylbenzidine) color development visualization analysis is carried out. Single-mode interference is effectively eliminated through double-signal independent output and cross validation, and the method is suitable for high-reliability detection of trace miRNA (such as a breast cancer marker miRNA-21) in complex samples such as serum. According to the invention, the defects of insufficient sensitivity (pM level), poor anti-interference performance and high platform complexity in the prior art are overcome, and an efficient tool is provided for early diagnosis of cancers.

The invention discloses a method for determining the DAR value of an antibody-conjugated drug. The method comprises the following steps: carrying out antibody capture, enzymolysis and detection on a to-be-detected sample; the enzymolysis is to carry out enzymolysis on the antibody coupling medicine by using at least one protease to obtain a characteristic peptide fragment of a CDR region and free micromolecule toxin; the antibody capture is to capture an antibody coupling drug in a sample by using a capture antibody. The problem of high background value during ADC detection in the prior art is solved, and the problem of poor sensitivity caused by high-resolution detection of a small molecule toxin antibody ratio (DAR) value can also be solved. Bioanalytical strategies associated with a range of pharmacokinetic (PK) and anti-drug antibody (ADA) assessments can be provided to producers.

The invention discloses a qualitative and quantitative detection method for the integrity of an AAV vector under multi-primer ITR design, and the detection method comprises the following steps: S1, designing a plurality of primers in a conserved region of an ITR sequence of the AAV vector, the length of the primers being 18-25bp, the Tm value being 55-65 DEG C, and the GC% being 40-60%; s2, carrying out validity inspection on the primer; s3, adopting a Multiplex LAM-PCR (Polymerase Chain Reaction) method, performing amplification and sequencing by using the primer to obtain a chimeric sequence of the ITR and the host genome screened by using a biological analysis method, namely obtaining information of an ITR breakpoint; s4, according to the information of the ITR breakpoints, carrying out statistics on the distribution condition of the ITR breakpoints in the ITR region to obtain a statistical table; and S5, obtaining a qualitative and quantitative result of the ITR fracture position according to the statistical table. According to the method, the number of chimeric sequences in each primer region is counted, and the ITR breakpoints are qualitatively judged and quantitatively analyzed, so that the integrity of the AAV vector is comprehensively evaluated.

The invention provides a full-automatic online detection method for trace polycyclic aromatic hydrocarbon derivatives (SPAHs) in water, which comprises the following steps: (1) pretreatment: standing a water sample, centrifugally filtering to remove suspended matters, adding a prepared mixed standard solution, and directly loading on a machine; (2) enrichment and separation: adopting a Turbo flow C18-XL on-line solid phase extraction column to realize automatic enrichment and matrix purification of the 15 SPAHs, and combining an ultra-high performance liquid chromatography gradient elution program (methanol-ultrapure water system) to realize efficient enrichment and separation; and (3) detection and analysis: performing Full MS-ddMS2 scanning in an APCI (Amplified Peripheral Component Interconnect) source-Orbitrap high-resolution mass spectrum positive and negative ion switching mode to realize synchronous detection of hydroxyl, nitro and oxygen-containing SPAHs. According to the method, a unified detection system covering six hydroxyl polycyclic aromatic hydrocarbons, six oxygen-containing polycyclic aromatic hydrocarbons and three nitro polycyclic aromatic hydrocarbons is constructed for the first time, the detection limit is as low as 0.02 ng / L, and compared with a traditional GC-MS method, the sensitivity is greatly improved, and the sample pretreatment time is greatly shortened. Compared with the prior art, derivatization treatment is not needed, continuous sample injection is achieved through an online solid-phase extraction column regeneration technology, complex matrix interference is effectively eliminated in cooperation with a dynamic elimination function, and a high-sensitivity and high-throughput analysis method is provided for ecological risk assessment of trace SPAHs in underground water and surface water.

One aspect provided herein is an analyte processing device, comprising one or more flow channels, wherein at least one flow channel of the one or more flow channels comprise an analyte processing area; one or more excitation sources in optical communication with the analyte processing area, and comprising an optical path from the one or more excitation sources to the analyte processing area; and one or more photodetectors in optical communication with the analyte processing area, wherein the optical path comprises a light scattering control system.

The invention relates to the technical field of oral medicine and biological information analysis, in particular to an evaluation system for oral microbiological analysis and decayed tooth risk prediction. The system comprises a sample collection module, a microorganism detection module, a data preprocessing module, a microorganism population dynamic analysis module, a multi-dimensional feature extraction module, a decayed tooth risk assessment module and a personalized suggestion generation module. By constructing microbial population evolution analysis based on a Lotka-Volterra competitive model, diversity dynamic change analysis based on Shannon entropy and evolution trend prediction based on a Lyapunov stability theory, the system deeply reveals a dynamic evolution law of an oral micro-ecosystem, and a multi-dimensional feature adaptive weighting mechanism based on mutual information is adopted, so that the dynamic evolution law of the oral micro-ecosystem is improved. Personalized accurate risk assessment is realized, a causal reasoning theory is introduced to generate personalized intervention suggestions with causal support, and the accuracy and the prevention effect of dental caries risk prediction are remarkably improved.

This invention provides a simple synthesis method for Fe-Ag / CMP nanopolymers with catalase-like activity and their application in hydrogen peroxide detection, belonging to the field of bioanalytical technology. The method of this invention includes the following steps: (1) preparing a 4-hydroxyethylpiperazine thiosulfonic acid (HEPES) standard buffer solution; (2) adding cytidine monophosphate (CMP) to the solution obtained in step (1) and stirring until the CMP is fully dissolved. Then, under vigorous stirring, ferric nitrate aqueous solution and silver nitrate aqueous solution are added sequentially, at which point the colorless solution turns pale yellow; (3) transferring the mixed solution obtained in step (2) to a centrifuge tube, centrifuging at 12000 rpm for 8 min to collect the precipitate, washing it three times with distilled water, and finally adding 4 mL of distilled water to obtain a 1 mg / mL Fe-Ag / CMP suspension. This invention utilizes CMP as a biological ligand and Ag... + Fe 3+ Simultaneous coordination, and the reducing amino groups on CMP can directly transfer Ag... + In situ reduction to silver nanoparticles (AgNPs) led to the one-step synthesis of a bimetallic Fe-Ag / CMP nanopolymer with hydrogen peroxide-like nanozyme activity, enabling the detection of hydrogen peroxide.

The present invention relates to an analysis device for biological analysis to detect the presence and / or concentration of a substance in a liquid contained in an analysis chamber of a cartridge. The analysis device specifically includes a piezoelectric vibration member equipped with detachable piezoelectric fingers.