Active targeting of dendritic cells with mannan-decorated PLGA 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
The purpose of this study was to identify an optimum targeted particulate formulation based on mannan (MN)-decorated poly(D, L-lactide-co-glycolide) (PLGA) nanoparticles (NPs), for efficient delivery of incorporated cargo to dendritic cells (DCs). In brief, NPs were formulated from two different types of PLGA; ester-terminated (capped) or COOH-terminated (uncapped) polymer. Incorporation of MN in NPs was achieved either through addition of MN during the process of NP formation or by attachment of MN onto the surface of the freeze dried NPs by physical adsorption or chemical conjugation (to COOH terminated polymer). The formulated NPs were characterized in terms of particle size, Zeta potential and level of MN incorporation. The effect of polymer type and the incorporation method on the extent of fluorescently labelled NP uptake by murine bone marrow-derived DCs have been investigated using flowcytometry. The results of this study showed MN incorporation to enhance the uptake of PLGA NPs by DCs. Among different MN incorporation strategies, covalent attachment of MN to COOH-terminated PLGA-NPs provided the highest level of MN surface decoration on NPs. Maximum NP uptake by DCs was achieved by COOH terminated PLGA NPs containing covalent or adsorbed MN. Therefore, a better chance of success for these formulations for active targeted drug and/or vaccine delivery to DCs is anticipated.
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 | 0.001 | 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 | 0.001 |
| 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