57 results about "Biological entity" patented technology

A computer-implemented method of training a machine learning model to identify biological entities for drug discovery is disclosed. The method comprises providing a training data set comprising a plurality of entity-linked text sequences, each text sequence including a mention of a biological entity, where the biological entity is linked to a corresponding biological entity identifier from a set of possible biological entity identifiers; masking the mention of the biological entity within each text sequence; encoding each masked text sequence into an input representation for a machine learning model; and training a machine learning model to predict the unique entity identifier of the masked biological entity based on the input representation. The described method is able to utilise the full breadth of the rich contextual information available in the biomedical text corpus to predict new biological targets for drug discovery and avoids the restrictions intrinsic to relationship prediction using knowledge graphs. The ability to identify more promising, biologically relevant targets in an automated manner, significantly reduces the requirement of human input and reduces the failure rate in targets that are progressed in the drug delivery pipeline.

This disclosure provides a novel method and system for characterizing morphodynamic profiles of objects, such as biological entities. This disclosure provides a shape, appearance, and motion (SAM) phenotype Observation Tool (SPOT). SPOT establishes a standardized SAM “phenome,” image descriptors resembling single-cell transcriptomes, to comprehensively quantify a cell's instantaneous state without prior knowledge. SPOT also establishes a standardized workflow for temporal analysis. SPOT is a generalist tool, applicable to any live-cell imaging and advances biomedical discovery through its standardized, unbiased, streamlined workflow to quantify phenotypic heterogeneity and predict phenotype-genotype-function coupling.

The invention belongs to the technical field of biological data processing, and discloses a multi-omics data fusion method and system based on a hypergraph network. According to the method, a hypergraph structure is adopted for modeling omics data, high-order interaction information can be more efficiently mined, and a complex association mode between biological entities can be more comprehensively revealed; by introducing a hypergraph aggregation mechanism, high-order complex relationships in various omics data can be represented more accurately, the limitation that a traditional method can only capture the relationship between every two nodes is overcome, and the understanding ability of the model to the interaction between biological entities is improved; according to the hypergraph fusion method, multi-omics specific hypergraphs are effectively integrated, unified representation of cross-omics data is realized, the representation capability of the model for complex multi-relational data is enhanced, and more comprehensive technical support is provided for multiple downstream tasks.

The present invention concerns a method of performing one or more reactions on a biological entity, the method comprising: (i) isolating the biological entity in a microcapsule comprising a core and a semi-permeable shell; and (ii) performing the one or more reactions on the biological entity in the microcapsule.

A device for detecting and identifying a living or non-living entity includes a real entity unit equipped on an element that is to be detected and identified. At least one detection module is equipped on another element configured to detect the real entity unit, which broadcasts, in a unidirectional manner and without dialogue and in loops, a real image or a virtual image or an avatar of the entity to be detected and information or attributes associated with an identity of the entity. The real entity unit includes a storage and / or digital recording means, a power supply internal means, remote reception means, capture means, and broadcasting means. Each detection module is equipped with reception means, temporary storage means, displaying or listening means, and processing means for processing the data.

This disclosure provides a microfluidic system (e.g., microfluidic cartridge, microfluidic chip) comprising two or more microfluidic flow channels for impedance-based detection of a biological entity in a sample. The disclosed system enables simultaneous measurements of a sample in two or more microfluidic flow channels to minimize faulty results. It eliminates the need of lysing samples and measuring them multiple times that is more time-consuming, and could introduce some variations across samples and devices.

The invention discloses a characterization alignment space-based drug-target interaction prediction method and device. The method comprises the following steps of: initializing parameters of a protein characterization dimension, a drug characterization dimension, a public embedding characterization dimension, the number of layers of a multi-layer sensor and a batch dimension; acquiring a plurality of single-source network data through a plurality of pharmaceutical databases, and performing comparison processing to construct a biological medicine heterogeneous network; according to a comparative learning strategy, integrating a protein target and drug characterization into a public embedding characterization space, and carrying out DTI association training to set a model; and inputting the protein targets and the corresponding drug representations into the trained setting model for DTI prediction to obtain a plurality of most relevant drugs. According to the method, by constructing the biological medicine heterogeneous network, the DTI association related to unknown medicines can be predicted; an embedded characterization alignment frame is built, a high-quality characterization method can be utilized to characterize a biological medicine network and a biological entity, and the problem of training data sparsity can be solved by utilizing contrast loss.

A bioengineering method which comprises introducing an inert nucleic acid cassette into a biological entity without introducing or modifying characteristics or traits in the biological entity. The method comprises receiving or providing a sample comprising the biological entity having a nucleic acid sequence; selecting an integration site in the nucleic acid sequence for inserting the inert nucleic acid cassette; designing the inert cassette with optimized primer sequences, optimized probe sequences, optimized stop codons and disrupted start codons, and inserting the inert nucleic acid cassette into the biological entity at the integration site; and validating that no characteristics have been added or modified in the biological entity.

The invention discloses a biomolecular interaction prediction method based on multi-modal attention fusion, and belongs to the technical field of artificial intelligence drug discovery. The method comprises the following steps: acquiring multi-modal characteristics of drugs, targets, diseases and genes: sequence structure characteristics, 3D structure characteristics, similarity network characteristics and biological relation network embedding characteristics; constructing a feature fusion prediction model, and performing training; inputting the multi-modal features of the two biological entities into the trained feature fusion prediction model, and outputting the probability of interaction of the two biological entities; the feature fusion prediction model comprises a Transform encoder and an MLP (Markup Language Protocol) network; the multi-modal features are input into a feature fusion prediction model for stacking and then are input into a Transform encoder, the features are processed by using a multi-head self-attention mechanism, and an output result is flattened and subjected to dimension reduction processing to obtain embedded vector representation; and finally, performing element corresponding multiplication on the embedded vectors of the two biological entities, inputting the embedded vectors into an MLP network, and outputting an interaction probability between the two biological entities.

An implantable membrane construct including a maximum pore size (MPS) less than 2 microns and opposing sides, each side of the construct having a surface roughness (Sa) greater than about 0.5 microns is disclosed. When the luminal surface of the implantable membrane construct has a surface roughness (Sa) greater than about 0.5 microns, mesenchymal cells do not form at the interface of the lumen and the first layer (i.e., luminal interface) such that the mesenchymal cells do not impede the flow of oxygen and nutrients to the graft cells (when implanted). When implanted, the outermost layer of the implantable membrane construct enables cellular penetration, vascularization, and anchoring of the construct. The implantable membrane construct includes single layer embodiments and multiple layer embodiments. Encapsulation devices utilizing the implantable membrane constructs to encapsulate biological entities (e.g., cells) into a patient are also provided.

A biocompatible membrane composite including a cell impermeable layer and a mitigation layer is provided. The cell impermeable layer is impervious to vascular ingrowth and prevents cellular contact from the host. Additionally, the mitigation layer includes solid features. In at least one embodiment, mitigation layer has therein bonded solid features. In some embodiments, the cell impermeable layer and the mitigation layer are intimately bonded or otherwise connected to each other to form a composite layer having a tight / open structure. A reinforcing component may optionally be positioned external to or within the biocompatible membrane composite to provide support to and prevent distortion. The biocompatible membrane composite may be used in or to form a device for encapsulating biological entities, including, but not limited to, pancreatic lineage type cells such as pancreatic progenitors.

An implantable membrane structure is disclosed that includes a maximum aperture (MPS) of less than 2 microns and opposing sides, each side of the structure having a surface roughness (Sa) of greater than about 0.5 microns. When the surface roughness (Sa) of the lumen surface of the implantable membrane structure is greater than about 0.5 microns, mesenchymal cells do not form at the interface of the lumen and the first side, i.e., the lumen interface, so that the mesenchymal cells do not hinder flow of oxygen and nutrients to transplanted cells (when implanted). When implanted, the outermost layer of the implantable membrane structure enables cell penetration, vascularization, and structural anchoring. The implantable membrane structure includes a single layer embodiment and a multi-layer embodiment. Encapsulation devices for encapsulating biological entities (e.g., cells) into a patient using implantable membrane structures are also provided.

Systems and methods for flowing particles, such as biological entities, in a fluidic channel(s) are generally provided. In some cases, the systems described herein are designed such that a single particle may be isolated from a plurality of particles and flowed into a fluidic channel (e.g., a microfluidic channel) and / or collected e.g., on fluidically isolated surfaces. For example, the single particle may be present in a plurality of particles of relatively high density and the single particle is flowed into a fluidic channel, such that it is separated from the plurality of particles. The particles may be spaced within a fluidic channel so that individual particles may be measured / observed over time. In certain embodiments, the particle may be a biological entity. Such article and methods may be useful, for example, for isolating single cells into individual wells of multi-well cell culture dishes (e.g., for single-cell analysis).

The present invention relates to a diagnostic array that enables simultaneous detection and analysis of multiple target molecules in biological samples. This diagnostic device integrates various biological entities immobilized at distinct locations on a substrate with specific agents conjugated to these entities. The device produces detectable changes, such as colorimetric, fluorescent, or chemiluminescent signals, upon interaction with target molecules. A corresponding smartphone application captures and analyzes the results, providing immediate preliminary interpretations. This invention addresses the need for a comprehensive, user-friendly diagnostic tool suitable for point-of-care and home testing, ensuring secure data transmission for further professional analysis.

The invention discloses a biological entity multivariate association prediction system combining linear and nonlinear fusion matrix factorization, which relates to the technical field of biological entity multivariate association prediction and comprises a multivariate biological entity input module, a cross-modal feature extraction module, a dual-channel fusion matrix factorization module, a dynamic feature fusion device and a multivariate association prediction engine. According to the method, the limitation of a traditional biological entity association prediction method is broken through by fusing linear and nonlinear matrix decomposition technologies, and a dynamic feature fusion mechanism realizes optimal combination of cross-modal features through adaptive weight adjustment, so that the problem of insufficient flexibility of a traditional static fusion strategy is overcome; in addition, the system adopts a three-dimensional tensor modeling technology, a unified prediction framework of multiple types of associations such as gene-disease, drug-target, metabolite-pathway and the like is realized, heterogeneity characteristics of biological associations can be effectively maintained, and compared with the prior art, the analysis capability of a complex biological network is remarkably improved.

A computer-implemented method is provided of analysing an image of a tissue specimen, which method comprises steps including detecting in the image each of a primary type of biological entity, detecting in the image one or more secondary types of biological entity, associated with each of the detected primary biological entities, generating an entity graph, in which each graph node is assigned to a primary biological entity, and in which each graph node is associated with predictive features measured from the image in respect of that graph node, including at least one predictive feature that is measured relative to two or more types of biological entity.

A device is provided for facilitating the imaging of biological entities. The device includes a body having upper and lower surfaces. The body defines a channel for accommodating fluid flow therethrough and a well communicating with the channel and the lower surface. A microscopy grid is removably received in the body and has a first side communicating with the channel and a second side directed at well. A retainer extends into the channel and is engageable with the microscopy grid to support the microscopy grid.

Embodiments include methods, systems, and computer program products for detecting probe microparticle(s). One such embodiment applies an electric field to a biological entity. The electric field includes multiple frequencies. One or more of the multiple frequencies correspond to respective types of probe microparticles. Each type of probe microparticle includes a core and at least a partial metal oxide coating. Further, each type of probe microparticle is configured to produce a response corresponding to a respective frequency and conjugate to a corresponding type of biological entity. Responsive to applying the electric field, a response signal is measured. Then, based on the measured response signal, a presence or absence of probe microparticle(s) conjugated to the biological entity is detected.

The application provides a method for monitoring the effect of a drug on the interaction between a biological body and a fluorescent probe, the method comprising: continuously injecting a first solution comprising a fluorescent probe into a fluorescent chamber and a microfluidic chamber of a microfluidic chip; the fluorescent probe is at least one in kind; at a first time, continuously injecting a solution comprising the fluorescent probe and a drug into the fluorescent chamber and the microfluidic chamber; the drug is at least one in kind; based on the imaging information corresponding to the fluorescent chamber and the microfluidic chamber at each time unit respectively, determining the effect of the drug on the interaction between the biological body and the fluorescent probe; wherein the microfluidic chamber comprises the biological body.

Methods, systems, devices, and machine-readable media for reducing biological carryover are disclosed. An exemplary method includes: generating an alternating electromagnetic field; and introducing an aspiration and dispensing device into the electromagnetic field. The exemplary method also includes: inductively heating the aspiration and dispensing device using the electromagnetic field to at least denature or inactivate at least one of a protein or a biological entity on a surface of the aspiration and dispensing device.

A monitoring device (1) comprises a microwell plate (10) comprising microwells (20) dimensioned to hold a respective biological entity and a channel plate (30) comprising at least one fluid channel (40, 42) in fluid connection with a fluid input port (11; 11A, 11B) and a fluid output port (13; 13A, 13B). An optode composition (25) is present in the microwells (20) and comprising an analyte-sensitive optode compound generating a detectable optical signal in response to an analyte. The channel plate (30) and the microwell plate (10) are slidably arranged together and movable relative to each other between a loading position, in which the at least one fluid channel (40, 42) is in fluid connection with at least a subset (21, 23) of the plurality of microwells (25), and a monitoring position, in which the channel plate (30) closes the at least a subset (21, 23) of the plurality of microwells (20).

The invention provides a biological enlightenment relation triple combined extraction method based on a fine-tuning large language model, and solves the problems of error propagation, difficulty in entity definition and insufficiency in chain dependence modeling in the prior art. The method comprises the following steps: constructing a full-chain bionic field corpus through reverse tracing, generating an initial triple label by using an advanced teacher model, and performing manual verification; and based on the selected base model, reconstructing the extraction task into a text generation task by adopting LoRA fine tuning to realize end-to-end joint extraction. According to the method, a composite entity boundary is accurately analyzed through field fine tuning, and error propagation is avoided; explicitly modeling chained dependence of'biological entity-bionic model-bionic application '; and few-sample field self-adaption is realized. Through accuracy verification, the extraction accuracy and logic consistency of the complex bionic text are remarkably improved, and technical support is provided for constructing a high-quality biological enlightenment knowledge base.

A biocompatible membrane composite including a first layer (cell impermeable layer), a second layer (a mitigation layer), and a third layer (a vascularization layer) is provided. The mitigation layer may be positioned between the cell impermeable layer and the vascularization layer In some embodiments, the cell impermeable layer and the mitigation layer are intimately bonded to form a composite layer having a tight / open structure. A reinforcing component may optionally be positioned on either side of the biocompatible membrane composite or within the biocompatible membrane composite to provide support to and prevent distortion of the membrane composite. The biocompatible membrane composite may be used in or to form a device for encapsulating biological entities, including, but not limited to, pancreatic lineage type cells such as pancreatic progenitors.

Disclosed is a biological entity for treating brain tumors, particularly gliomas, and a vector comprising the biological entity. The biological entity is a construct comprising at least an anti-tumor transgene, which is composed of at least one GluA knockdown agent, preferably at least two GluA knockdown agents, and preferably further comprises a fusion protein, an anti-PD-1 antibody, an anti-CTLA-4 antibody, and an immune response promoter of IL12. The vector comprises a wild-type HSV-1 virus, and the biological entity replaces the ICP34.5 gene of the wild-type HSV-1 virus. The vector comprising the wild-type HSV-1 virus modified with the biological entity shows little negative effect on neurons, while showing positive effect on human glioblastoma cells, both when neuronal cells and glioblastoma cells are cultured separately and when co-cultured.

The invention relates to the field of additive manufacturing, in particular to electrode ink based on a biological entity and a preparation method and application of the electrode ink. The preparation method of the electrode ink based on the biological entity comprises the following steps: performing degreasing pretreatment on the biological entity to obtain a degreased biological entity; uniformly mixing the degreased biological entity with a binder and a structure reinforcing phase to obtain a mixture; and mixing and grinding the mixture and water to obtain the electrode ink based on the biological entity, the biological entity is plant pollen. The electrode ink provided by the invention has a biological entity with relatively high loading capacity, and can provide sufficient ion transmission gap channels; the electrode ink disclosed by the invention has good printable performance, and can keep a stable structure after pyrolysis and carbonization without cracking, and an electrode precursor frame prepared by printing is controllable in form, good in formability and high in stability.

This invention belongs to the field of biological data processing technology and discloses a multi-omics data fusion method and system based on hypergraph networks. This invention uses a hypergraph structure to model omics data, enabling more efficient mining of high-order interaction information and a more comprehensive revelation of complex relationship patterns between biological entities. By introducing a hypergraph aggregation mechanism, it can more accurately represent the high-order complex relationships within various omics data, overcoming the limitations of traditional methods that can only capture pairwise node relationships, and improving the model's ability to understand the interactions between biological entities. This hypergraph fusion method effectively integrates multi-omics-specific hypergraphs, achieving a unified representation of cross-omics data, enhancing the model's ability to represent complex multi-relationship data, and providing more comprehensive technical support for various downstream tasks.

In a first aspect, the present invention relates to a computer-implemented method for obtaining information about a biological entity based on at least one biological sequence, comprising: (a) providing a repository of fingerprint data strings for a biological sequence database, each fingerprint data string representing a characteristic biological subsequence composed of sequence units, each characteristic biological subsequence having a combination number less than the total number of different sequence units available in the biological sequence database, the combination number of the biological subsequence being defined as the number of different sequence units that appear as consecutive sequence units of the biological subsequence in the biological sequence database; (b) determining one or more fingerprint data strings representative of the biological entity; (c) searching a repository including information associated with the fingerprint data strings for information associated with the one or more representative fingerprint data strings; and (d) processing the information.

The present disclosure provides a metal and biological body detection device, system and method, comprising a detection coil, a comb-shaped capacitor and a signal generator connected in series, the detection coil is placed in overlap with the comb-shaped capacitor; the signal generator is used to provide an electrical signal with a set resonant frequency for the detection coil and the comb-shaped capacitor. The comb-shaped capacitor can output a larger parameter change when detecting a biological body, can amplify the change at both ends of the coil, realize the detection of the biological body, and at the same time, the detection coil is provided to realize the detection of a metal object, the detection coil is placed in overlap with the comb-shaped capacitor, which can cover the same detection area, and the integrated setting realizes the detection of the metal and the biological body.