1. A composition comprising:
a nanoparticle or microparticle comprising a biodegradable, amphiphilic, copolymer that self-aggregates to form a structure with a hydrophobic interior and a hydrophilic outer surface; and
a biomolecule covalently linked to the nanoparticle or microparticle;
wherein the covalent link between the biomolecule and the nanoparticle or microparticle comprises a ring formed by a Diels Alder cycloaddition or a Huisgen 1,3-dipolar cycloaddition reaction between a first unsaturated functional group attached to the polymer and a second, complementary, unsaturated functional group attached to the biomolecule.
2. The composition of claim 1 wherein said first and second unsaturated functional groups which react with each other by said Diels-Alder cycloaddition include a diene and a dienophile, and wherein said first and second unsaturated functional groups which react with each other by said Huisgen 1,3-dipolar cycloaddition include an alkyne group and an azide group.
3. The composition according to claim 2 wherein said diene is selected from the group consisting of furan and derivatives thereof, cyclopentadiene and derivatives thereof, butadiene and derivatives thereof, and cyclohexadiene and derivatives thereof, and wherein said dienophile is selected from the group consisting of maleimide and derivatives thereof, acrylonitrile and derivatives thereof, acrylamide and derivatives thereof, methyl vinyl ketone and derivatives thereof, esters of maleic acid and derivatives thereof, esters of fumaric acid and derivatives thereof, esters of acrylic acid and derivatives thereof, maleic anhydride and derivatives thereof, esters and amides of but-2-ynedioic acid and derivatives thereof, quinone and derivatives thereof, and substituted acetylenes and derivatives thereof.
4. The composition according to claim 2 wherein said diene is furan and said dienophile is maleimide.
5. The composition according to claim 2 wherein said alkyne group is selected from the group consisting of terminal alkynes and alkynes substituted with alkyl groups and derivatives thereof, ester groups and derivatives thereof, amide groups and derivatives thereof, alkyl and polyoxoalkyl groups and derivatives thereof, aryl groups and derivatives thereof, phenyl groups and derivatives thereof, and benzyl groups and derivatives thereof, and wherein said azide group is selected from the group consisting of alkyl and polyoxoalkyl azides and derivatives thereof, aryl azides and derivatives thereof, and benzyl azides and derivatives thereof.
6. The composition according to claim 5 wherein said alkyne group is an amide of propargylamine, and said azide is a substituted benzyl azide.
7. The composition of claim 1, wherein the biodegradable, amphiphilic, copolymer is selected from the group consisting of block copolymers, terpolymers, graft copolymers, and graft terpolymers.
8. The composition of claim 1 wherein the biodegradable, amphiphilic, copolymer is selected from the group consisting of polymers of natural origin, polymers produced by chemical synthesis and polymers produced by biological synthesis, and wherein said polymers of natural origin are selected from the group consisting of proteins, polysialic acids, hyaluronic acid and derivatives thereof, polysaccharides and derivatives thereof, chitosan and derivatives thereof, alginate and derivatives thereof, collagen and derivatives thereof, and aliphatic poly(esters), polycarbonates and derivatives thereof, poly(hydroxyalkanoates) and derivatives thereof, and wherein said polymers produced by biological synthesis include polymers synthesized by fermentation, and wherein said polymers produced by chemical synthesis include polymers produced by ring-open polymerization, polycondensation, free radical polymerization, or ionic polymerization.
9. The composition of claim 1 wherein said biodegradable copolymer is selected from the group consisting of polyesters, polycarbonates, polyamides, poly(esteramide)s, poly(anhydride)s, polyurethanes, poly(ester-urethane)s, poly(hydroxyalkanoate)s, and combinations thereof.
10. The composition according to claim 1 wherein said microparticle or nanoparticle comprises one or more therapeutic agents encapsulated in said interior of said polymer microparticle or polymer nanoparticle.
11. The composition according to claim 1 wherein said biomolecule is covalently bound to said outer surface of said microparticle or nanoparticle.
12. The composition according to claim 1 wherein said Huisgen 1,3-dipolar cycloaddition is Cu(1) catalyzed.
13. The composition according to claim 1, wherein the nanoparticle or polymer microparticle is a nanosphere.
14. The composition according to claim 1, wherein the nanoparticle or polymer microparticle is a microsphere.
15. The composition according to claim 1, wherein the biodegradable, amphiphilic, copolymer is a poly(trimethylene carbonate)-based copolymer.
16. The composition according to claim 1, wherein the biodegradable, amphiphilic, copolymer is a poly(lactide)-based copolymer.
17. The composition according to claim 16, wherein the biodegradable, amphiphilic, copolymer comprises a poly(ethylene glycol) segment.
18. The composition according to claim 1, wherein the copolymer is an aliphatic polyester copolymer.
19. The composition according to claim 1, wherein the copolymer is a polycarbonate copolymer.
20. The composition according to claim 1, wherein the copolymer is a block copolymer or a graft copolymer.
21. The composition according to claim 1, wherein the copolymer comprises hydrophilic and hydrophobic domains.
22. The composition according to claim 1, wherein the copolymer is a terpolymer.
23. The composition according to claim 1, wherein the nanoparticle or microparticle is a nanoparticle.
24. The composition according to claim 23, wherein the nanoparticle or microparticle is a nanoparticle with a size of about 200 nm or less.
25. The composition according to claim 1, wherein the nanoparticle or microparticle is a microparticle.
26. The composition according to claim 1, wherein the biomolecule is a therapeutic biomolecule.
27. The composition according to claim 1, wherein the biomolecule is a peptide, polypeptide or protein.
28. The composition according to claim 1, wherein the biomolecule is a nucleic acid.
29. The composition according to claim 1, wherein the biomolecule is an antibody or fragment thereof.
30. A composition comprising:
a nanoparticle or microparticle-comprising a polymer wherein said polymer is a poly(2-methyl-2-carboxytrimethylene carbonate-co-lactide)-graft-poly(ethylene glycol) polymer or a poly(2-allyloxymethyl-2-methyl-trimethylene carbonate-co-lactide) polymer;
a biomolecule covalently linked to the nanoparticle or microparticle;
wherein the covalent link between the biomolecule and the nanoparticle or microparticle comprises a ring formed by a Diels Alder cycloaddition or a Huisgen 1,3-dipolar cycloaddition reaction between a first unsaturated functional group attached to the polymer and a second, complementary, unsaturated functional group attached to the biomolecule.
31. The composition according to claim 30, wherein said polymer is a poly(2-methyl-2-carboxytrimethylene carbonate-co-lactide)-graft-poly(ethylene glycol) polymer.
32. The composition according to claim 31, wherein first unsaturated functional group attached to the polymer comprises a furan ring, a terminal alkyne group, or an azide group.
33. The composition according to claim 30, wherein said polymer is a poly(2-allyloxymethyl-2-methyl-trimethylene carbonate-co-lactide) polymer.
34. The composition according to claim 33, wherein the first unsaturated functional group attached to the polymer comprises a furan ring.
35. A method of delivering a biomolecule into a biological system comprising introducing a composition according to claim 1 into the biological system.
36. A method of delivering a biomolecule to an animal comprising administering to the animal a composition according to claim 1.
37. A method of delivering a biomolecule to a human comprising administering to the human a composition according to claim 1.
The claims below are in addition to those above.
All refrences to claim(s) which appear below refer to the numbering after this setence.
1. A method of annotating an image, comprising:
scoring the image using a plurality of trained classifiers, wherein each of the trained classifiers corresponds to at least one of a plurality of image groups clustered based upon image similarity, and wherein each image group is associated with a set of weighted labels,
wherein each of the weighted labels includes a label and an associated weight, and wherein the associated weight is determined based upon the frequency of occurrence of the label in the image group;
selecting one or more of the image groups based upon the scoring;
aggregating one or more sets of weighted labels associated with the selected one or more image groups; and
annotating the image using the aggregated one or more sets of weighted labels.
2. A method of annotating an image, comprising:
scoring the image using a plurality of trained classifiers, wherein each of the trained classifiers corresponds to at least one of a plurality of image groups clustered based upon image similarity, and wherein each image group is associated with a set of weighted labels;
selecting one or more of the image groups based upon the scoring;
aggregating one or more sets of weighted labels associated with the selected one or more image groups;
training a plurality of classifiers to create the plurality of trained classifiers, wherein at least one of the classifiers is trained for each of the respective image groups; and
annotating the image using the aggregated one or more sets of weighted labels.
3. The method of claim 2, wherein each of the plurality of classifiers is trained using a linear model.
4. The method of claim 2, wherein a classifier from the plurality of classifiers is trained for a selected one of the image groups using a positive training sample and a negative training sample, wherein the positive training sample comprises images from the selected group, and wherein the negative training sample comprises images from neighboring groups of the selected group.
5. The method of claim 4, wherein the negative training sample comprises images from neighboring groups of the selected group and images from all other groups of the image groups.
6. A method of annotating an image, comprising:
scoring the image using a plurality of trained classifiers, wherein each of the trained classifiers corresponds to at least one of a plurality of image groups clustered based upon image similarity, and wherein each image group is associated with a set of weighted labels,
wherein the scoring the image comprises assigning, corresponding to respective ones of the image groups, a score to the image based upon a distance of a set of features of the image to a set of features representative of the image group;
selecting one or more of the image groups based upon the scoring;
aggregating one or more sets of weighted labels associated with the selected one or more image groups; and
annotating the image using the aggregated one or more sets of weighted labels.
7. A method of annotating an image, comprising:
scoring the image using a plurality of trained classifiers, wherein each of the trained classifiers corresponds to at least one of a plurality of image groups clustered based upon image similarity, and wherein each image group is associated with a set of weighted labels;
selecting one or more of the image groups based upon the scoring, wherein the selecting one or more of the groups comprises filtering ones of the plurality of image groups that have a score of less than a threshold;
aggregating one or more sets of weighted labels associated with the selected one or more image groups; and
annotating the image using the aggregated one or more sets of weighted labels.
8. A system for annotating an image, comprising:
a processor;
a memory coupled to the processor;
a classification and scoring module configured to execute on the processor and further configured to:
score an image using a plurality of trained classifiers, wherein each of the trained classifiers corresponds to at least one of a plurality of image groups clustered based upon image similarity, and wherein each image group is associated with a set of weighted labels,
wherein each of the weighted labels includes a label and an associated weight, and wherein the associated weight is determined based upon the frequency of occurrence of the label in the image group; and
select one or more of the image groups based upon the scoring; and
a label aggregator module configured to execute on the processor and further configured to:
aggregate one or more sets of weighted labels associated with the selected one or more image groups; and
annotate the image using the aggregated one or more sets of weighted labels.
9. A system for annotating an image, comprising:
a processor;
a memory coupled to the processor;
a classification and scoring module configured to execute on the processor and further configured to:
score an image using a plurality of trained classifiers, wherein each of the trained classifiers corresponds to at least one of a plurality of image groups clustered based upon image similarity, and wherein each image group is associated with a set of weighted labels;
select one or more of the image groups based upon the scoring,
wherein the classification and scoring module is further configured to train a plurality of classifiers to create the plurality of trained classifiers, wherein at least one of the classifiers is trained for each of the respective image groups; and
a label aggregator module configured to execute on the processor and further configured to:
aggregate one or more sets of weighted labels associated with the selected one or more image groups; and
annotate the image using the aggregated one or more sets of weighted labels.