Phase Separation‐Induced Surface Protuberances in Hydrogel Particles for Enhanced Intestinal Retention
Bibliographic record
Abstract
The surface roughness of microparticles enhances their biological interactions; however, engineering such features in fully assembled polymeric membranes remains challenging. Inspired by natural budding phenomena, this study developed solvent-free tannic acid-polyethylene oxide (TA-PEO) microcapsules with tunable surface roughness, achieved through an interfacial instability mechanism triggered by bovine serum albumin (BSA). The microfluidic platform enables precise control of microcapsule size and monodispersity through vibration frequency and flow rate optimization. The dynamic hydrogen-bonded TA-PEO network facilitates pH-responsive drug release, which can be tuned from burst to sustained modes through polyethylene oxide (PEO) concentration adjustments. Competitive BSA adsorption at the capsule interface generates localized "soft patches," triggering spontaneous budding under osmotic gradients. This roughness significantly enhances intestinal adhesion, with budding microcapsules exhibiting prolonged retention in vivo compared with their smooth counterparts. In a mouse model of inflammatory bowel disease (IBD) induced by dextran sulfate sodium (DSS), probiotic-loaded budding microcapsules restored colon length, epithelial integrity, and body weight, outperforming free probiotics and non-budding controls. In summary, this study established a solvent-free strategy for engineering adhesive rough-surfaced microcapsules, highlighting their potential for targeted mucosal delivery and gastrointestinal therapeutics.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".