Study on the Secondary Structure and Immunogenicity of Sulfonated Silk Fibroin
Bibliographic record
Abstract
Silk fibroin was used as the material for preparing sulfonated silk fibroin(SSF) by means of diazonium salt coupling.The spectrum of SSF treated with different organic solvents was obtained by attenuated total reflectance-Fourier transformed infrared spectrum(ATR-FTIR).The proportional variation of various SSF secondary structures was assessed through Fourier self-deconvolution(FSD),second derivative and curve fitting.Moreover,animal test was conducted to analyze its immunogenicity so as to explore practical value of SSF in medical tissue engineering.The proportion of β-sheet,random coil,α-form and β-turn in lyophilized SSF was found to be 10.97%±1.32%,59.92%±2.72%,17.50%±2.13%,and 11.61%±1.17%,respectively.After being treated with different organic alcohol solutions,the SSF had various rates in secondary structure change which showed a slow-down trend with treatment time.After organic alcohol treatment,the random-coil secondary structure was transformed into α-form of Silk I type and then transformed into more stable β-sheet of Silk II type.Nevertheless,random coil and α-form could be converted into each other in different solvents.Stimulatory reaction test in mouse spleen cells(T-and B-cells) revealed that SSF has low immunogenicity.The results show that SSF has low immunogenicity and its secondary structure is adjustable by organic alcohol,being promising for development of tissue engineering material with excellent biocompatibility and biodegradablility for slow and controlled release of drug.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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 teacher head, 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".