<i>In Situ</i> Interfacial Super-Assembly of Nanobiohybrids through Plant for Food-Grade Oral Medicine
Bibliographic record
Abstract
Developing a next-generation oral drug delivery system with enhanced efficacy and limited side effects is highly desired for refractory diseases treatment such as colitis. The bioinspired assembly of drugs within food-grade plants highlights its potential value of this unique hybrid material. Herein, we report the preparation of drug-encapsulated vegetable nanobiohybrid superassembled frameworks as an oral food-grade drug delivery system (SAF-FGDD). The in situ superassembly of SAF-FGDD driven by natural transpiration from living plants is carried out through a sustainable and low-carbon manner, allowing for the assembly of distinct precursors inside edible living plants. As an example, mesalazine, an anti-inflammatory drug, is encapsulated in the frameworks for colitis treatment. The cell activity and feeding experiments of zebrafish and mice demonstrate the excellent efficacy of this SAF-FGDD. Compared with those of the control groups, the disease activity index scores and histological scores of the SAF-FGDD group were significantly decreased by 80% and 98%, respectively. The improved performance is attributed to the biocompatibility and protective effect of SAF-FGDD, allowing for abundant mesalazine to be released and act at the site of the intestine during the process of food digestion. In combination with mature soilless cultivation technology, plant-based organisms with natural structure-forming abilities possess broad commercial prospects in large-scale production of various food-grade functional materials.
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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 | 0.000 |
| Open science | 0.001 | 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".