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Patent Agency Ranking
1.发明申请公开(公告)号：US20220218465A1
公开(公告)日：2022-07-14
申请号：US17502152
申请日：2021-10-15
Inventor： Hyeon Ji KIM , Dong Woo CHO , Jin Ah JANG
IPC: A61F2/14 , A61L27/36 , A61L27/38 , B29C64/106
Abstract: A modified extracellular matrix-based hydrogel according to an example of the present disclosure includes an extracellular matrix-denatured collagen conjugate formed by a Michael addition reaction between an extracellular matrix having an amine group and a denatured collagen into which an ethylenically unsaturated bond functional group is introduced. The modified extracellular matrix-based hydrogel according to the present disclosure exhibits enhanced mechanical properties (e.g., viscoelasticity) compared to the extracellular matrix hydrogel before modification. In addition, it shows a high cell viability when the bioink is prepared by encapsulating cells in a modified extracellular matrix-based hydrogel according to the present disclosure. In addition, when an artificial living tissue for transplantation (for example, artificial corneal tissue) manufactured by 3-D printing bioink according to the present disclosure is transplanted into a damaged cornea, it can be sutured and has a transparency similar to that of the real cornea, and corneal tissue can be reconstructed without other side effects due to its enhanced mechanical properties. Accordingly, the modified extracellular matrix-based hydrogel according to the present disclosure can be applied in tissue engineering fields and related fields requiring improvement in physical properties and is particularly useful as a material for corneal transplants.
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公开(公告)号：US20250061111A1
公开(公告)日：2025-02-20
申请号：US18725248
申请日：2021-12-30
Inventor： Wook Shin HAN , Hyuk Kyu KANG , Hyeon Ji KIM
IPC: G06F16/242 , G06F16/21
Abstract: A learning data set enhancing method comprises the steps of: determining a first initial learning data set comprising a first learning-purpose natural language query, database information regarding the database, and a first learning-purpose SQL query corresponding to the first learning-purpose natural language query; generating first novel database information regarding a first novel database having a different schema from the database by applying a first schema modification operation to the database; generating a first novel learning-purpose SQL query regarding the first novel database by applying a first SQL query synchronization operation corresponding to the first schema modification operation to the first learning-purpose SQL query; and determining a first novel learning data set comprising the first learning-purpose natural language query, the first novel database information, and the first novel learning-purpose SQL query.
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3.发明申请公开(公告)号：US20250058017A1
公开(公告)日：2025-02-20
申请号：US18721363
申请日：2022-03-14
Inventor： Jin Ah JANG , Hyeon Ji KIM , Seung Hyeon HWANG
Abstract: One embodiment of the present disclosure provides an extracellular matrix-based hybrid ink for 3D printing, the hybrid ink including an extracellular matrix having an amine group and a modified hyaluronic acid introduced with an ethylenically unsaturated bond functional group, in which the extracellular matrix and the modified hyaluronic acid are in a crosslinked state by a chemical bond formed between at least some of amine groups present in the extracellular matrix and the ethylenically unsaturated bond functional group present in the modified hyaluronic acid. According to an embodiment of the present disclosure, the hybrid ink has mechanical properties suitable for 3D printing through chemical crosslinking between the extracellular matrix and modified hyaluronic acid as constituents, and can control the drug release rate by adjusting the chemical crosslinking density.
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公开(公告)号：US20230111780A1
公开(公告)日：2023-04-13
申请号：US17936385
申请日：2022-09-29
Applicant: POSTECH Research and Business Development Foundation , Konkuk University Industrial Cooperation Corp
Inventor： Hyeon Ji KIM , Je Hwan JANG , Won Il HAN , Joon Young KIM , Jin Ah JANG , Dong Woo CHO
Abstract: An embodiment of the present disclosure provides an extracellular matrix-based bioadhesive as an adhesive in the form of a composition including an extracellular matrix-containing hydrogel and a gelatin curing agent, wherein the extracellular matrix-containing hydrogel is gelatinized. Since the extracellular matrix-based bioadhesive according to an embodiment of the present disclosure has the same or similar rheological properties as gelatin, the bioadhesive has flowability at a temperature of 30° C. or higher and may be evenly and easily applied to a lesion site in the body. In addition, the extracellular matrix-based bioadhesive according to an embodiment of the present disclosure may adhere well to the lesion site because of a level of adhesive strength that is about 2 to 6 times higher than that of fibrin glue used as a commercial tissue adhesive. In addition, the extracellular matrix-based bioadhesive according to an embodiment of the present disclosure is based on a tissue-derived extracellular matrix, and thus includes a tissue-derived wound healing component or a tissue regeneration component, and may be used for wound healing or tissue regeneration in addition to bioadhesive applications.
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5.发明公开公开(公告)号：US20230169075A1
公开(公告)日：2023-06-01
申请号：US17964807
申请日：2022-10-12
Inventor： Wook Shin HAN , Hyuk Kyu KANG , Hyeon Ji KIM
IPC: G06F16/2452 , G06F16/242
CPC classification number: G06F16/24522 , G06F16/2433
Abstract: Disclosed is a natural language query processing apparatus comprising, a processor that receives a natural language query input by a user and generates a structured query based on the natural language query, wherein the processor, when generating the structured query based on the natural language query, generates the structured query using a natural language processing result for the natural language query, a schema relationship extracted based on a relationship between subdatabases in a database related to the natural language query, and a cross-attention result generated between the natural language processing result and the schema relationship.
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