Construction and applications of exosome-microneedle integrated systems
Bibliographic record
Abstract
With the rapid advancement of drug delivery technologies, microneedles (MNs) have emerged as a novel transdermal delivery platform due to their ease of administration, minimally invasive nature, and high efficiency. MNs have demonstrated broad applicability for delivering diverse therapeutic agents, including small molecules, nucleic acids, peptides, and proteins. Exosomes (Exos), a class of extracellular vesicles with unique biological functions and significant clinical potential, have attracted increasing attention in recent years. However, their widespread application is limited by issues such as poor stability, low delivery efficiency, and potential safety and immune risks. The integration of Exos with MNs (Exos-MNs) systems offers a promising strategy to address these challenges. This review provides a comprehensive overview of recent advances in Exos-MNs delivery systems, including the technological advances of MNs, biological characteristics and engineering strategy of Exos, and the construction strategies of Exos-MNs. Additionally, we highlight recent developments in the application of Exos-MNs systems and discuss future perspectives and challenges for their clinical translation.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".