A radically simple, ingestible colorimetric biosensor pill for cost-effective, non-invasive monitoring of intestinal inflammation
Bibliographic record
Abstract
Inflammatory bowel diseases (IBDs) affect millions worldwide, necessitating frequent monitoring of intestinal inflammation to optimize treatment strategies. However, current fecal calprotectin tests have low patient adherence, limiting their utility for inflammation monitoring. Here, we developed an ingestible biosensor for simplified at-home detection of a key inflammation biomarker—reactive oxygen species (ROS). Our pill for ROS-responsive inflammation monitoring (PRIM) employs an ROS-responsive polymer that selectively degrades in the presence of ROS. Degradation triggers the release of blue dye into feces for a visually detectable readout without fecal sampling or laboratory analysis. In vitro , PRIM remained stable under healthy conditions and activated only at elevated ROS levels (10–50 mM H 2 O 2 ). In rats with colitis, the miniaturized PRIM demonstrated a sensitivity of 78% and a specificity of 72% in detecting intestinal inflammation. With further optimization, PRIM has the potential to improve accessibility and patient adherence to inflammation monitoring and enhance personalized disease management for IBD.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".