Abstract: The present disclosure relates to polymers which contain a hydrophobic and hydrophilic segment which is sensitive to pH. In some aspects, the polymers form a micelle which is sensitive to pH and results in a change in fluorescence based upon the particular pH. In some aspects, the disclosure also provides methods of using the polymers for the imaging of cellular or extracellular environment or delivering a drug.

Abstract: The present disclosure relates to polymers which contain a hydrophobic and hydrophilic segment which is sensitive to pH. In some aspects, the polymers form a micelle which is sensitive to pH and results in a change in fluorescence based upon the particular pH. In some aspects, the disclosure also provides methods of using the polymers for the imaging of cellular or extracellular environment or delivering a drug.

Abstract: Provided herein are block copolymers comprising a hydrophilic polymer segment and a hydrophobic polymer segment, wherein the hydrophilic polymer segment comprises a polymer selected from the group consisting of: poly(ethylene oxide) (PEO), poly(methacrylate phosphatidyl choline) (MPC), and polyvinylpyrrolidone (PVP), wherein the hydrophobic polymer segment comprises wherein R? is —H or —CH3, wherein R is —NR1R2, wherein R1 and R2 are alkyl groups, wherein R1 and R2 are the same or different, wherein R1 and R2 together have from 5 to 16 carbons, wherein R1 and R2 may optionally join to form a ring, wherein n is 1 to about 10, and wherein x is about 20 to about 200 in total. Also provided are pH-sensitive micelle compositions for therapeutic and diagnostic applications.

Abstract: One or more implementations of the present specification provide risk control of transactions based on a graphical structure model. A graphical structure model trained by using labeled samples is obtained. The graphical structure model is defined based on a transaction data network that includes nodes representing entities in a transaction and edges representing relationships between the entities. Each labeled sample includes a label indicating whether a node corresponding to the labeled sample is a risky transaction node. The graphical structure model is configured to iteratively calculate an embedding vector of the node in a latent feature space based on an original feature of the node or a feature of an edge associated with the node. An embedding vector of an input sample is calculated by using the graphical structure model. Transaction risk control is performed on the input sample based on the embedding vector.

Abstract: A graphical structure model trained by using labeled samples is obtained. The graphical structure model is defined based on an enterprise relationship network that includes nodes and edges. Each labeled sample includes a label indicating whether a corresponding node is a risky credit node. The graphical structure model is configured to iteratively calculate an embedding vector of at least one node in a hidden feature space based on an original feature of the at least one node and/or a feature of an edge associated with the at least one node. An embedding vector corresponding to a test-sample is calculated by using the graphical structure model. Credit risk analysis is performed on the test-sample. The credit risk analysis is performed based on a feature of the test-sample represented in the embedding vector. A node corresponding to the test-sample is labeled as a credit risk node.

Abstract: Provided herein are block copolymers comprising a hydrophilic polymer segment and a hydrophobic polymer segment, wherein the hydrophilic polymer segment comprises a polymer selected from the group consisting of: poly(ethylene oxide) (PEO), poly(methacrylate phosphatidyl choline) (MPC), and polyvinylpyrrolidone (PVP), wherein the hydrophobic polymer segment comprises wherein R? is —H or —CH3, wherein R is —NR1R2, wherein R1 and R2 are alkyl groups, wherein R1 and R2 are the same or different, wherein R1 and R2 together have from 5 to 16 carbons, wherein R1 and R2 may optionally join to form a ring, wherein n is 1 to about 10, and wherein x is about 20 to about 200 in total. Also provided are pH-sensitive micelle compositions for therapeutic and diagnostic applications.

Abstract: A graphical structure model trained with labeled samples is obtained. The graphical structure model is defined based on an account relationship network that comprises a plurality of nodes and edges. The edges correspond to relationships between adjacent nodes. Each labeled sample comprises a label indicating whether a corresponding node is an abnormal node. The graphical structure model is configured to iteratively calculate, for at least one node of the plurality of nodes, an embedding vector in a hidden feature space based on an original feature of the least one node and/or a feature of an edge associated with the at least one node. A first embedding vector that corresponds to a to-be-tested sample is calculated using the graphical structure model. Abnormal account prevention and control is performed on the to-be-tested sample based on the first embedding vector.

Abstract: The present disclosure relates to polymers which contain a hydrophobic and hydrophilic segment which is sensitive to pH. In some aspects, the polymers form a micelle which is sensitive to pH and results in a change in fluorescence based upon the particular pH. In some aspects, the disclosure also provides methods of using the polymers for the imaging of cellular or extracellular environment or delivering a drug.

Abstract: Provided herein are block copolymers comprising a hydrophilic polymer segment and a hydrophobic polymer segment, wherein the hydrophilic polymer segment comprises a polymer selected from the group consisting of: poly(ethylene oxide) (PEO), poly(methacrylate phosphatidyl choline) (MPC), and polyvinylpyrrolidone (PVP), wherein the hydrophobic polymer segment comprises wherein R? is —H or —CH3, wherein R is —NR1R2, wherein R1 and R2 are alkyl groups, wherein R1 and R2 are the same or different, wherein R1 and R2 together have from 5 to 16 carbons, wherein R1 and R2 may optionally join to form a ring, wherein n is 1 to about 10, and wherein x is about 20 to about 200 in total. Also provided are pH-sensitive micelle compositions for therapeutic and diagnostic applications.

Abstract: A graphical structure model trained with labeled samples is obtained. The graphical structure model is defined based on an account relationship network that comprises a plurality of nodes and edges. The edges correspond to relationships between adjacent nodes. Each labeled sample comprises a label indicating whether a corresponding node is an abnormal node. The graphical structure model is configured to iteratively calculate, for at least one node of the plurality of nodes, an embedding vector in a hidden feature space based on an original feature of the least one node and/or a feature of an edge associated with the at least one node. A first embedding vector that corresponds to a to-be-tested sample is calculated using the graphical structure model. Abnormal account prevention and control is performed on the to-be-tested sample based on the first embedding vector.

Abstract: A graphical structure model trained with labeled samples is obtained. The graphical structure model is defined based on an account relationship network that comprises a plurality of nodes and edges. The edges correspond to relationships between adjacent nodes. Each labeled sample comprises a label indicating whether a corresponding node is an abnormal node. The graphical structure model is configured to iteratively calculate, for at least one node of the plurality of nodes, an embedding vector in a hidden feature space based on an original feature of the least one node and/or a feature of an edge associated with the at least one node. A first embedding vector that corresponds to a to-be-tested sample is calculated using the graphical structure model. Abnormal account prevention and control is performed on the to-be-tested sample based on the first embedding vector.

Abstract: Provided herein are block copolymers comprising a hydrophilic polymer segment and a hydrophobic polymer segment, wherein the hydrophilic polymer segment comprises a polymer selected from the group consisting of: poly(ethylene oxide) (PEO), poly(methacrylate phosphatidyl choline) (MPC), and polyvinylpyrrolidone (PVP), wherein the hydrophobic polymer segment comprises wherein R? is —H or —CH3, wherein R is —NR1R2, wherein R1 and R2 are alkyl groups, wherein R1 and R2 are the same or different, wherein R1 and R2 together have from 5 to 16 carbons, wherein R1 and R2 may optionally join to form a ring, wherein n is 1 to about 10, and wherein x is about 20 to about 200 in total. Also provided are pH-sensitive micelle compositions for therapeutic and diagnostic applications.

Abstract: The present disclosure relates to polymers which contain a hydrophobic and hydrophilic segment which is sensitive to pH. In some aspects, the polymers form a micelle which is sensitive to pH and results in a change in fluorescence based upon the particular pH. In some aspects, the disclosure also provides methods of using the polymers for the imaging of cellular or extracellular environment or delivering a drug.

Abstract: Use of carrimycin in Mycobacterium tuberculosis infection resistance comprises the main steps: measuring the activity of carrimycin in Mycobacterium tuberculosis resistance by adopting an absolute concentration method through taking clinical first-line antituberculotics, i.e., isoniazid and rifampicin as controls. The result indicates that carrimycin has obvious superior activity to clinically-separated Mycobacterium tuberculosis including drug-resistant bacteria compared with those of the clinical first-line control drugs, i.e., the isoniazid and the rifampicin, and use of carrimycin in manufacturing drugs for treating tubercle Bacillus infected diseases are expected to be developed.

Abstract: The present disclosure provides a biosynthetic gene cluster of carrimycin. The biosynthetic gene cluster comprises 44 gene open reading frames (orf), i.e., 5 orfs (orf10-14) encoding polyketide synthase, 9 orfs (orf1, 4-6, 15 and 36-39) related to polyketone synthesis extension unit and modification, 16 orfs (orf9, 16-22, 24, 26, 28, 29, 33-35 and 41) related to glycosyl synthesis, 6 orfs (orf7, 8, 30-32 and 40) related to glycosyl transfer, 2 orfs (orf3 and 25) related to resistance, 4 orfs (orf2, 23, 27 and 42) possibly related to regulation, a tsr resistance marker gene orf (orf43) and a 4?-mycaroseglucoside isovaleryl transferase gene orf (orf44).

Abstract: Provided herein are block copolymers comprising a hydrophilic polymer segment and a hydrophobic polymer segment, wherein the hydrophilic polymer segment comprises a polymer selected from the group consisting of: poly(ethylene oxide) (PEO), poly(methacrylate phosphatidyl choline) (MPC), and polyvinylpyrrolidone (PVP), wherein the hydrophobic polymer segment comprises wherein R? is —H or —CH3, wherein R is —NR1R2, wherein R1 and R2 are alkyl groups, wherein R1 and R2 are the same or different, wherein R1 and R2 together have from 5 to 16 carbons, wherein R1 and R2 may optionally join to form a ring, wherein n is 1 to about 10, and wherein x is about 20 to about 200 in total. Also provided are pH-sensitive micelle compositions for therapeutic and diagnostic applications.

Abstract: Provided herein are block copolymers comprising a hydrophilic polymer segment and a hydrophobic polymer segment, wherein the hydrophilic polymer segment comprises a polymer selected from the group consisting of: poly(ethylene oxide) (PEO), poly(methacrylate phosphatidyl choline) (MPC), and polyvinylpyrrolidone (PVP), wherein the hydrophobic polymer segment comprises wherein R? is —H or —CH3, wherein R is —NR1R2, wherein R1 and R2 are alkyl groups, wherein R1 and R2 are the same or different, wherein R1 and R2 together have from 5 to 16 carbons, wherein R1 and R2 may optionally join to form a ring, wherein n is 1 to about 10, and wherein x is about 20 to about 200 in total. Also provided are pH-sensitive micelle compositions for therapeutic and diagnostic applications.

Abstract: Provided herein are block copolymers comprising a hydrophilic polymer segment and a hydrophobic polymer segment, wherein the hydrophilic polymer segment comprises a polymer selected from the group consisting of: poly(ethylene oxide) (PEO), poly(methacrylate phosphatidyl choline) (MPC), and polyvinylpyrrolidone (PVP), wherein the hydrophobic polymer segment comprises wherein R? is —H or —CH3, wherein R is —NR1R2, wherein R1 and R2 are alkyl groups, wherein R1 and R2 are the same or different, wherein R1 and R2 together have from 5 to 16 carbons, wherein R1 and R2 may optionally join to form a ring, wherein n is 1 to about 10, and wherein x is about 20 to about 200 in total. Also provided are pH-sensitive micelle compositions for therapeutic and diagnostic applications.

Abstract: A graphical structure model trained by using labeled samples is obtained. The graphical structure model is defined based on an enterprise relationship network that includes nodes and edges. Each labeled sample includes a label indicating whether a corresponding node is a risky credit node. The graphical structure model is configured to iteratively calculate an embedding vector of at least one node in a hidden feature space based on an original feature of the at least one node and/or a feature of an edge associated with the at least one node. An embedding vector corresponding to a test-sample is calculated by using the graphical structure model. Credit risk analysis is performed on the test-sample. The credit risk analysis is performed based on a feature of the test-sample represented in the embedding vector. A node corresponding to the test-sample is labeled as a credit risk node.

Abstract: One or more implementations of the present specification provide risk control of transactions based on a graphical structure model. A graphical structure model trained by using labeled samples is obtained. The graphical structure model is defined based on a transaction data network that includes nodes representing entities in a transaction and edges representing relationships between the entities. Each labeled sample includes a label indicating whether a node corresponding to the labeled sample is a risky transaction node. The graphical structure model is configured to iteratively calculate an embedding vector of the node in a latent feature space based on an original feature of the node or a feature of an edge associated with the node. An embedding vector of an input sample is calculated by using the graphical structure model. Transaction risk control is performed on the input sample based on the embedding vector.