Hybrid Hydrogel-Magnet Actuated Capsule for Automatic Gut Microbiome Sampling
Bibliographic record
Abstract
OBJECTIVE: Non-invasive, pill-sized capsules can provide intestinal fluid sampling to easily retrieve site-specific gut microbiome samples for studies in nutrition and chronic diseases. However, capsules with both automatic sampling and active locomotion are uncommon due to limited onboard space. This paper presents a novel hybrid hydrogel-magnet actuated capsule featuring: i) pH-responsive hydrogels that will automatically trigger fluid sampling at an environmental pH of 6 and ii) active locomotion by an external rotating magnetic field. METHOD: Two capsule designs were fabricated (Design A: 31 μL sampling volume with dimensions 8 mm × 19 mm, Design B: 41 μL sampling volume with dimensions 8 mm × 21 mm). They were immersed in simulated gastric (pH = 1.2) and simulated intestinal fluid (pH = 6.8) to test for automatic intestinal fluid sampling. An external rotating magnetic field was applied to test for active locomotion. Finally, seal tests were performed to demonstrate sample contamination mitigation. RESULTS: Preliminary experiments showed that sampling occurred quickly and automatically in simulated intestinal fluid at 6-15 hours, active locomotion via rotation, rolling, and tumbling were possible at magnetic field magnitudes 10 mT, oil piston seals were better at mitigating sample contamination than water piston seals, and minimum o-ring seal pressures limits of 1.95 and 1.69 kPa for Design A and B respectively were sufficient against intra-abdominal pressures. SIGNIFICANCE: This work presents the ability to impart capsule multi-functionality in a compact manner without onboard electronics or external triggering for sampling.
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 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".