Lymph Node‐Targeted Nanomaterials for Controlled Nano‐Immunotherapy
Bibliographic record
Abstract
Lymph nodes (LNs), as critical components of the lymphatic system, serve as the primary site for adaptive immune responses and represent important therapeutic targets for various diseases. Studies demonstrate that LN metastasis of malignant tumors constitutes a major cause of mortality in cancer patients, highlighting the crucial importance of achieving precise drug accumulation in LNs for enhanced therapeutic efficacy. While significant progress has been made in optimizing lymph‐targeting capabilities through rational design of nanoparticle‐based drug delivery systems, the immunological mechanisms and regulatory pathways involved remain to be fully elucidated. This review focuses on elucidating the interaction mechanisms between nanoparticles and immune cells within LNs through investigating the distribution, retention, and immunomodulatory effects of nanodrugs. By integrating tumor microenvironment characteristics, we aim to precisely regulate the targeted delivery behavior of nanoparticles, thereby advancing the development of enhanced cancer immunotherapy.
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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".