Two-Step Enzymatic Synthesis of Biocompatible Polymers Made from Cholic Acid
Bibliographic record
Abstract
Polyesters are known biodegradable materials that are frequently used for biomedical applications that require biocompatibility. Their synthesis usually requires transition metal catalysts, which may become a source of contamination. In addition, using such compounds translates to extensive purification procedures, which do not agree with green chemistry principles. In addition to being renewable, enzymes such as lipases are milder for biological systems, and were studied for both ring-closure and ring-opening reactions. Here, Candida antarctica lipase B was used in ring-closure, reducing a two-step synthesis to a single step with 58% yield. The bile acid-containing macrocycles were subsequently polymerized with the same enzyme; relatively high molar masses (40 000 g/mol) were obtained. The conditions for the enzymatic ring-closure and ring-opening reactions were established through the reaction of thapsic acid with 1,10-decanediol. The di- and tetralactones afforded semicrystalline polymers with relatively high molar masses. Therefore, lipases were successfully used for both ring-closing reactions and ring-opening polymerizations of large rigid moieties as well as more flexible structures. The use of enzymes for the multistep syntheses shows their utility as a simple and green method for monomer and polymer synthesis with better biocompatibility and tunable properties.
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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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".