Bacteriophage-loaded microneedle patches for targeted and minimally disruptive foodborne pathogen decontamination
Bibliographic record
Abstract
Antibacterial additive use has surged because of rising incidences of food contamination despite concerns over antibiotic resistance. Bacteriophage (bacterial viruses) is a promising alternative with pathogen-level specificity. However, their commercial success has been limited by the considerable diffusion barriers they face within food, preventing effective delivery at contamination sites. Here, we introduce bacteriophage-loaded microneedle patches that enable targeted phage delivery directly within food, eliminating internal pathogens in a minimally disruptive manner. The application of microneedles within food is first explored. The platform is then substantiated by comparing performance in raw beef and cooked chicken, where we achieved up to 3-log reduction in Escherichia coli , meeting regulatory limits. In contrast, conventional surface application of the same phage failed to provide statistically significant decontamination. To ensure broad applicability, phage cocktails were also loaded into microneedles to demonstrate polymicrobial decontamination. This platform can also be adapted to extend food shelf-life by targeting spoilage-inducing bacteria.
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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".