β‐1,3 Glucan Microparticles & Nanoparticles: Fabrication Methods & Applications in Immunomodulation & Targeted Drug Delivery
Bibliographic record
Abstract
Innate immune cells such as macrophages and dendritic cells play major roles in the progression of many cancerous, fibrotic, and autoimmune diseases, often due to environmental cues that skew these cells toward a phenotype that progresses or exacerbates the disease state. As such, a growing focus in treating such diseases is placed on exploiting the high plasticity of these cells to modify or reverse their pro-disease phenotypes using immunomodulatory materials. β-1,3 glucans are one such type of material that has exhibited diverse immunomodulatory effects on immune cells, including the mitigation or reversal of the adverse effects of dysregulated immune cells. In this review, we outline various fabrication techniques to produce β-1,3 glucan-derived microparticles and nanoparticles and discuss the diverse particle properties that can be obtained by tuning glucan chemistry, fabrication method, and formulation components. Furthermore, the immunomodulatory applications of β-1,3 glucan particles are highlighted with a focus on immune cell targeting, modulation, and the delivery of small molecule and macromolecular therapeutics.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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) | 0.002 | 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".