Effect of Matrix Aging on the Behavior of Human Serum Albumin Entrapped in a Tetraethyl Orthosilicate-Derived Glass
Bibliographic record
Abstract
The steady-state and time-resolved fluorescence of Trp-214 was used to examine the conformation, dynamics, accessibility, thermal stability, and degree of ligand binding of human serum albumin (HSA) after entrapment of the protein in sol−gel processed glasses. The bioglasses were derived from tetraethyl orthosilicate and were aged in air without washing (dry-aged), in air after a washing step (washed), or in buffer (wet-aged). In all cases, significant changes were observed in the structure and dynamics of HSA, consistent with adsorption of the protein onto the silica surface combined with partial unfolding of the protein. Significant changes in the thermal stability and degree of ligand binding of the entrapped protein were also observed, with both stability and ligand binding capacity decreasing as aging continued. All proteins showed full accessibility to neutral quenchers over 2 months of aging but only partial accessibility to negatively charged quenchers, even at early aging times, indicating electrostatic repulsion of such analytes by the negatively charged matrix. Taken together, the results indicated that the reduced ligand binding for entrapped HSA was caused by a combination of protein denaturation and partial inaccessibility of the protein to negatively charged species. After 2 months of aging the entrapped proteins retained less than 15% of their binding ability in solution, regardless of which method was used to age the material. In light of these results, it is clear that improved sol−gel processing methods will be needed to overcome the time-dependent changes in the structure and function of proteins entrapped in silicate-based glasses.
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) | 0.001 | 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 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".