Immune responses of therapeutic lipid nanoparticles
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Nanoparticle-based drug delivery is an emerging technology for targeting therapeutics to the diseased site for enhanced therapy and reduced toxicity. A number of pharmaceutical products that involve nanotechnology have been approved for clinical use, and because of altered pharmacokinetics and biodistribution, their profiles of interaction with host cells and resulting toxicity are different from parent agents. This review focuses on the immune responses induced by therapeutic lipid nanoparticles. These immune responses can provoke toxicity, affect pharmacokinetics of the nanoparticles or induce therapeutic effect. This article begins with a general introduction on immune responses and innate and acquired immunity. Specific examples of therapeutic lipid nanoparticles inducing immune responses in each category are presented with detailed discussions on the mechanisms. Current guidelines for evaluating immune response of nanomedicines are summarized. Finally, perspectives and future directions are provided emphasizing mechanistic studies of immune reactions triggered by nanoparticles.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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) | 0.000 | 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 it