Triggered degradation of poly(ester amide)s via cyclization of pendant functional groups of amino acid monomers
Bibliographic record
Abstract
Poly(ester amide)s (PEAs) are of interest for a diverse range of applications as their structures and properties can be readily tuned through the incorporation of a wide variety of monomers. In this work, the incorporation of the amino acids L-2,4-diaminobutyric acid (DAB) and homocysteine (HCY) was investigated with the aim of imparting stimuli-responsive degradation properties to PEAs. First, small molecule model compounds were prepared and studied to demonstrate that upon revealing the pendant γ-amine or γ-thiol of DAB and HCY esters, intramolecular cyclizations to 5-membered lactams and thiolactones respectively were much more rapid than background ester hydrolysis. Subsequently, monomers containing these DAB and HCY self-immolative spacers were prepared and incorporated into PEAs such that cleavage of protecting groups on the pendant moieties by stimuli including acid and the reducing agent DTT induced cyclization reactions that directly cleaved esters in the PEA backbone. The degradation of these polymers both in solution and in films was studied, demonstrating stimuli-triggered degradation was more rapid than background polymer degradation. In addition, to demonstrate that the approach could be readily extended to various stimuli, a photochemically responsive PEA was prepared by simply changing the protecting group on the pendant amine. This intramolecular cyclization strategy involving pendant functional groups should therefore be useful for the development of a wide range of PEAs and other polymers for which it is desirable to initiate degradation under specified conditions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".