Biodegradable nanoparticle delivery of a Th2-biased peptide for induction of Th1 immune responses
Bibliographic record
Abstract
The type of immune response developed against the hepatitis B virus (HBV) is crucial in determining the outcome of the disease. The protective effects of vaccine-induced antibody responses against subsequent exposure to HBV are well-established. After the establishment of chronic HBV infection, cell-mediated immune response is curative while humoral response is detrimental. A therapeutic vaccine that could switch the type of response could lead to disease resolution. Hepatitis B core antigen (HBcAg)(129-140) has been identified as a Th2-biased peptide in H-2(b) mice when it is administered along with complete Freund's adjuvant (CFA). We formulated HBcAg(129-140) along with monophosphoryl lipid A in poly(D,L-lactic-co-glycolic acid) (PLGA) nanoparticles. Naive mice immunized with the nanoparticle formulation developed a strong Th1-type response while mice immunized with the control formulation of CFA and peptide did not. We then primed mice with CFA and peptide to establish a Th2-type immune response before administering the nanoparticle formulation. Mice receiving the nanoparticle formulation being primed with CFA still developed a strong Th1-type response, while mice that received incomplete Freund's adjuvant and peptide instead of nanoparticles did not. The ability of PLGA nanoparticles to alter the type of immune response elicited by a peptide, even in the context of an ongoing immune response, makes PLGA nanoparticles a strong candidate for the formulation of therapeutic vaccines.
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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".