Microfluidic Synthesis of Ginseng Polysaccharide Nanoparticles for Immunostimulating Action on Macrophage Cell Lines
Bibliographic record
Abstract
) has become of increasing scientific interest because of its immune-enhancing properties. Herein, we have developed a novel approach to synthesize ginseng polysaccharide nanoparticles (NPs) from NA ginseng for enhancing their immunostimulation. Nanoparticles of ginseng polysaccharide were prepared using a microfluidic device and compared to other conventional wet chemical processes including nanoprecipitation and reverse microemulsion. The morphology and size of the NPs were characterized by SEM, TEM, DLS and FTIR. Depending on the experimental conditions, microfluidics was found to provide unimodal polysaccharide spheres down to 20 nm (±4 nm) with very narrow particle size distributions. In addition, the immunostimulating effect of the polysaccharide NPs was investigated on Murine macrophage cell lines, with the results revealing an enhanced production of all proinflammatory mediators in a concentration dependent manner. The proposed microfluidic system has the advantages of ease of fabrication, simplicity, and a fast and low-cost process that is capable of producing ginseng polysaccharide NPs with demonstrated enhancement of immunostimulation of macrophage cell lines.
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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) | 0.000 | 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 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".