Impact of Ultrasound-Treated Emulsion Gels on the Structure of Purees for Oropharyngeal Dysphagia
Bibliographic record
Abstract
This study investigated the effects of inulin concentration and ultrasonic homogenization on the particle size distribution and microstructure of oil-in-water emulsion gels stabilized with psyllium husk. These gels were then incorporated into meal purees formulated for individuals with dysphagia. Under ultrasound treatment, an increase in inulin from 0% to 20% reduced the average droplet size from 14.98 μm to 1.58 μm, indicating a synergistic effect between ultrasound treatment and inulin in reducing and stabilizing droplet size. The optimal formulation under ultrasound was 20% (w/w) inulin. Scanning electron and polarized light microscopy confirmed that ultrasonic homogenization improved emulsion integrity by minimizing droplet size and promoting encapsulation. Inulin-rich emulsion gels, when added to purees, reduced structural voids, improved matrix cohesion, and lowered expressible fluid content. Enzymatic assays showed enhanced inhibition of α-amylase and α-glucosidase, indicating increased resistance to oral enzymatic degradation. Importantly, substituting emulsion gels at 10% (w/w) did not compromise puree firmness. All formulations met International Dysphagia Diet Standardization Initiative (IDDSI) Level 4 requirements, confirming their suitability for individuals with oropharyngeal dysphagia (OD). These findings demonstrate the potential of psyllium husk-stabilized emulsion gels as innovative texture-modifying agents for dysphagia-friendly food development.
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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".