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Structural analysis of photocrosslinkable methacryloyl-modified protein derivatives

2017· article· en· W2620260189 on OpenAlexfundno aff
Kan Yue, Xiuyu Li, Karsten Schrobback, Amir Sheikhi, Nasim Annabi, Jeroen Leijten, Weijia Zhang, Yu Shrike Zhang, Dietmar W. Hutmacher, Travis J. Klein, Ali Khademhosseini

Bibliographic record

VenueBiomaterials · 2017
Typearticle
Languageen
FieldMaterials Science
TopicElectrospun Nanofibers in Biomedical Applications
Canadian institutionsnot available
FundersNational Institute of Arthritis and Musculoskeletal and Skin DiseasesNational Cancer InstituteInstitute for Future Environments, Queensland University of TechnologyNational Science FoundationCanadian Institutes of Health ResearchNational Heart, Lung, and Blood InstituteScience and Technology Commission of Shanghai MunicipalityDivision of Materials ResearchAustralian Research CouncilNederlandse Organisatie voor Wetenschappelijk OnderzoekOffice of Naval ResearchNational Natural Science Foundation of ChinaQueensland University of TechnologyNational Institutes of Health
KeywordsGelatinMethacrylamideSelf-healing hydrogelsMethacrylatePolymer chemistryBioconjugationPhotopolymerMaterials scienceSurface modificationMethacrylic acidGlycidyl methacrylateChemistryCombinatorial chemistryOrganic chemistryPolymerizationPolymerAcrylamideCopolymer

Abstract

fetched live from OpenAlex

Biochemically modified proteins have attracted significant attention due to their widespread applications as biomaterials. For instance, chemically modified gelatin derivatives have been widely explored to develop hydrogels for tissue engineering and regenerative medicine applications. Among the reported methods, modification of gelatin with methacrylic anhydride (MA) stands out as a convenient and efficient strategy to introduce functional groups and form hydrogels via photopolymerization . Combining light-activation of modified gelatin with soft lithography has enabled the materialization of microfabricated hydrogels. So far, this gelatin derivative has been referred to in the literature as gelatin methacrylate , gelatin methacrylamide , or gelatin methacryloyl, with the same abbreviation of GelMA. Considering the complex composition of gelatin and the presence of different functional groups on the amino acid residues, both hydroxyl groups and amine groups can possibly react with methacrylic anhydride during functionalization of the protein. This can also apply to the modification of other proteins, such as recombinant human tropoelastin to form MA-modified tropoelastin (MeTro). Here, we employed analytical methods to quantitatively determine the amounts of methacrylate and methacrylamide groups in MA-modified gelatin and tropoelastin to better understand the reaction mechanism. By combining two chemical assays with instrumental techniques, such as proton nuclear magnetic resonance ( 1 H NMR) and liquid chromatography tandem-mass spectrometry (LC-MS/MS), our results indicated that while amine groups had higher reactivity than hydroxyl groups and resulted in a majority of methacrylamide groups, modification of proteins by MA could lead to the formation of both methacrylamide and methacrylate groups. It is therefore suggested that the standard terms for GelMA and MeTro should be defined as gelatin methacryloyl and methacryloyl-substituted tropoelastin, respectively, to remain consistent with the widespread abbreviations used in literature.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.033
GPT teacher head0.330
Teacher spread0.297 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations210
Published2017
Admission routes1
Has abstractno

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