Oral Administered Particulate Yeast-Derived Glucan Promotes Hepatitis B Virus Clearance in a Hydrodynamic Injection Mouse Model
Bibliographic record
Abstract
Hepatitis B virus (HBV) persistent infection is associated with ineffective immune response for the clearance of virus. Immunomodulators represent an important class of therapeutics, which potentially could be beneficial for the treatment of HBV infection. The particulate yeast-derived glucan (PYDG) has been shown to enhance the innate and adaptive immune responses. We therefore, assessed the efficacy of PYDG in enhancing HBV specific immune responses by employing the hydrodynamic injection-based (HDI) HBV transfection mouse model. Mice were intragatric administered PYDG daily for 9 weeks post pAAV/HBV1.2 hydrodynamic injection. PYDG treatment significantly promoted HBV DNA clearance and production of HBsAb compared to control mice. PYDG treatment resulted in recruitment of macrophages, dendritic cells (DCs) and effector T cells to the liver microenvironment, accompanied by a significantly augmented DCs maturation and HBV-specific IFN-γ and TNF-α production by T cell. In addition, enhanced production of Th1 cytokines in liver tissue interstitial fluid (TIF) was associated with PYDG administration. Live imaging showed the accumulation of PYDG in the mouse liver. Our results demonstrate that PYDG treatment significantly enhances HBV-specific Th1 immune responses, accompanied by clearance of HBV DNA, and therefore holds promise for further development of therapeutics against chronic hepatitis B.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".