Release of fluorescent markers from phase‐separated gelatin‐maltodextrin hydrogels
Bibliographic record
Abstract
Abstract Genipin‐crosslinked gelatin‐maltodextrin phase‐separated hydrogels consisting of gelatin‐continuous or bicontinuous microstructures were developed to regulate swelling and release behavior of four fluorescent markers of varying molecular weights [(fluorescein (332 Da) and FITC‐dextrans (FD) (4000–250,000 Da)]. Bicontinuous hydrogels showed significantly greater swelling than gelatin‐continuous hydrogels under all conditions (at pH 1.5 and 7.4 and three genipin/gelatin crosslinking ratios) ( P < 0.05). With both microstructures, fluorescein showed the largest release rate and total release followed by FD 4000 Da, FD 40,000 Da, and FD 250,000 Da ( P < 0.05). Marker molecular weight, pH, and crosslink ratio all affected the rate and amount of release. The mode of transport for the solvent and all markers was Fickian or slightly anomalous, with diffusional exponent ( n ) values ranging from 0.35 to 0.64. These results demonstrated that with the proper combination of crosslink density, solvent pH, and microstructure, hydrogels with a specified swelling behavior may be developed. This, coupled with a marker of appropriate size, can lead to controllable levels and rates of release. © 2011 Wiley Periodicals, Inc. J Appl Polym Sci, 2011
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 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) | 0.000 | 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 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".