Engineering temperature‐sensitive poly(<i>N</i>‐isopropylacrylamide) polymers as carriers of therapeutic proteins
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This study was carried out to engineer N-isopropylacrylamide (NiPAM) polymers that contain protein-reactive N-acryloxysuccinimide (NASI) and hydrophobic alkylmethacrylates (AMAs). These thermoreversible, protein-conjugating polymers hold potential for retention of therapeutic proteins at an application site where tissue regeneration is desired. The lower critical solution temperatures (LCST) of the polymers were effectively controlled by the AMA mole content. The AMAs with longer side-chains were more effective in lowering the LCST. Polymers without NASI exhibited a stable LCST in phosphate buffer and in serum over a 10-day study period. The LCST of polymers containing NASI was found to increase over time in phosphate buffer, but not in serum-containing medium. The LCST increase in phosphate buffer was proportional to the AMA content. The feasibility of localizing a therapeutic protein, recombinant human bone morphogenetic protein-2 (rhBMP-2), to a site of application was explored in a rat intramuscular injection model. The results indicated that polymers capable of conjugating to rhBMP-2 were most effective in localizing the protein irrespective of the LCST (13-25 degrees C). For polymers with no NASI groups, a lower LCST resulted in a better rhBMP-2 localization. We conclude that thermosensitive polymers can be engineered for delivery of therapeutic proteins to improve their therapeutic efficacy.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it