Biodegradable Nanoneedles for Localized Delivery of Nanoparticles <i>in Vivo:</i> Exploring the Biointerface
Bibliographic record
Abstract
Nanoneedles display potential in mediating the delivery of drugs and biologicals, as well as intracellular sensing and single-cell stimulation, through direct access to the cell cytoplasm. Nanoneedles enable cytosolic delivery, negotiating the cell membrane and the endolysosomal system, thus overcoming these major obstacles to the efficacy of nanotherapeutics. The low toxicity and minimal invasiveness of nanoneedles have a potential for the sustained nonimmunogenic delivery of payloads in vivo, provided that the development of biocompatible nanoneedles with a simple deployment strategy is achieved. Here we present a mesoporous silicon nanoneedle array that achieves a tight interface with the cell, rapidly negotiating local biological barriers to grant temporary access to the cytosol with minimal impact on cell viability. The tightness of this interfacing enables both delivery of cell-impermeant quantum dots in vivo and live intracellular sensing of pH. Dissecting the biointerface over time elucidated the dynamics of cell association and nanoneedle biodegradation, showing rapid interfacing leading to cytosolic payload delivery within less than 30 minutes in vitro. The rapid and simple application of nanoneedles in vivo to the surface of tissues with different architectures invariably resulted in the localized delivery of quantum dots to the superficial cells and their prolonged retention. This investigation provides an understanding of the dynamics of nanoneedles' biointerface and delivery, outlining a strategy for highly local intracellular delivery of nanoparticles and cell-impermeant payloads within live tissues.
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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".