Photoimmobilization of biomolecules within a 3-dimensional hydrogel matrix
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
It has been recognized that a three-dimensional cell invasive scaffold that provides both topographical and chemical cues is desirable in regenerative tissue engineering to encourage cell attachment, migration, regrowth and ultimately tissue repair. Carbohydrate hydrogels are attractive for such applications because they are generally biocompatible and able to match the mechanical properties of most soft tissues. Although carbohydrate hydrogels have been previously modified with cell adhesive peptides and proteins, complicated hydrogel matrix activation was required prior to biomolecule coupling and, perhaps more importantly, the overall immobilization yield was low at approximately 1%. In this study, we report the photo-immobilization of a model biomolecule, ovalbumin (OVA), to agarose gel. We describe two methods of modification where the photoactive moiety is coupled to either the protein (i.e. OVA) or the matrix (i.e. agarose) prior to immobilization. We found that the photo-immobilization yield depends on the location of the photoactive moiety. Using photoactive OVA, 1.8% of the OVA initially incorporated into the agarose gel is immobilized; using photoactive agarose, 9.3% of the OVA initially mixed with the agarose is immobilized. The latter is a significant improvement over previous yields and may be useful in attaining our goal of immobilizing a biomolecule gradient for guided tissue regeneration.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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 it