Visible light crosslinkable human hair keratin hydrogels
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
Keratins extracted from human hair have emerged as a promising biomaterial for various biomedical applications, partly due to their wide availability, low cost, minimal immune response, and the potential to engineer autologous tissue constructs. However, the fabrication of keratin-based scaffolds typically relies on limited crosslinking mechanisms, such as via physical interactions or disulfide bond formation, which are time-consuming and result in relatively poor mechanical strength and stability. Here, we report the preparation of photocrosslinkable keratin-polyethylene glycol (PEG) hydrogels via the thiol-norbornene "click" reaction, which can be formed within one minute upon irradiation of visible light. The resulting keratin-PEG hydrogels showed highly tunable mechanical properties of up to 45 kPa in compressive modulus, and long-term stability in buffer solutions and cell culture media. These keratin-based hydrogels were tested as cell culture substrates in both two-dimensional surface seeding and three-dimensional cell encapsulation, demonstrating excellent cytocompatibility to support the attachment, spreading, and proliferation of fibroblast cells. Moreover, the photocrosslinking mechanism makes keratin-based hydrogel suitable for various microfabrication techniques, such as micropatterning and wet spinning, to fabricate cell-laden tissue constructs with different architectures. We believe that the unique features of this photocrosslinkable human hair keratin hydrogel promise new opportunities for their future biomedical applications.
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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 | 0.001 | 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 it