Protein-based micro- and nano-transporters for gut microbiota modulators: advances in delivery strategies and gut health benefits
Bibliographic record
Abstract
Human gut microbiota (GM) is essential for gut health, and its dysbiosis is associated with diseases such as inflammatory bowel disease, obesity, and cancers. Natural GM modulators, including probiotics, bioactive phytochemicals, and peptides, have shown great potential in restoring microbial balance. However, their effectiveness is limited by stability, bioavailability, and targeted delivery to the gut. Protein-based micro- and nano-transporters have recently emerged as innovative platforms capable of overcoming these delivery barriers and improving the therapeutic performance of natural GM modulators. Here, we critically review the design strategies, functional performance, and therapeutic outcomes of various protein-based carriers, including composite hydrogels, stimuli-responsive microgels, targeted nanocomplexes, mucoadhesive microcapsules, and electrospun nanofibers. Furthermore, we discuss how these advanced systems ameliorate gut dysbiosis, modulate immune responses, enhance intestinal barrier integrity, and promote beneficial microbial growth. Finally, current challenges and future perspectives for clinical translation are outlined. Overall, this review aims to provide a mechanistic and practical foundation for the development of next-generation protein-based transporters for microbiota-targeted therapies.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".