Comparison of Physicochemical Properties of Native Mucus and Reconstituted Mucin Gels
Bibliographic record
Abstract
Simulating native mucus with model systems such as gels made from reconstituted mucin or commercially available polymers presents experimental advantages including greater sample availability and reduced inter- and intradonor heterogeneity. Understanding whether these gels reproduce the complex physical and biochemical properties of native mucus at multiple length scales is critical to building relevant experimental models, but few systematic comparisons have been reported. Here, we compared bulk mechanical properties, microstructure, and biochemical responses of mucus from different niches, reconstituted mucin gels (with similar pH and polymer concentrations as native tissues), and commonly used commercially available polymers. To evaluate gel properties across these length scales, we used small-amplitude oscillatory shear, single-particle tracking, and microaffinity chromatography with small analytes. With the exception of human saliva, the mechanical response of mucin gels was qualitatively similar to that of native mucus. The transport behavior of charged peptides through native mucus gels was qualitatively reproduced in gels composed of corresponding isolated mucins. Compared to native mucus, we observed substantial differences in the physicochemical properties of gels reconstituted from commercially available mucins and the substitute carboxymethylcellulose, which is currently used in artificial tear and saliva treatments. Our study highlights the importance of selecting a mucus model system guided by the length scale relevant to the scientific investigation or disease application.
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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) | 0.000 | 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 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".