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Record W2288654204 · doi:10.1139/cjpp-2015-0528

Vaccine adjuvant ginsenoside Rg1 enhances immune responses against hepatitis B surface antigen in mice

2016· article· en· W2288654204 on OpenAlexvenueno aff
Yuan Ding, Qin Yuan, Qianqian Cui, Chaoqi Liu, Zhiyong Zhou, Hai-Xia Zhao, Yaoyan Dun, Ting Wang, Changcheng Zhang

Bibliographic record

VenueCanadian Journal of Physiology and Pharmacology · 2016
Typearticle
Languageen
FieldMedicine
TopicHepatitis B Virus Studies
Canadian institutionsnot available
FundersChina Three Gorges University
KeywordsHBsAgAdjuvantImmune systemSplenocyteImmunologyAntigenHepatitis B vaccineTLR4AntibodyInterferonMedicineHepatitis B virus

Abstract

fetched live from OpenAlex

The adjuvant effect of ginsenoside Rg1 on immune responses against hepatitis B surface antigen (HBsAg) in mice was investigated. Female BALB/c mice were subcutaneously injected with saline or HBsAg antigen with or without Rg1 on days 7 and 21. Samples were collected 2 weeks after the boosting for the detection of anti-HBsAg immunoglobulin G (IgG) isotypes in sera and gamma interferon (IFN-γ) and interleukin-4 (IL-4) produced in splenocytes. The innate and adaptive immune responses were measured in mice immunized as described above. The results showed that ginsenoside Rg1 had adjuvant properties in stimulating IgG, splenocyte proliferation, and mRNA expression of cytokines IFN-γ and IL-4, as well as the expression of cell surface marker TLR4 in the HBsAg-immunized mice. These results indicate that Rg1 enhances both Th1 (IgG2b and IFN-γ) and Th2 (IgG1 and IL-4) responses. In addition, the TLR4 signaling pathway is involved in the adjuvant activities of ginsenoside Rg1.

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.425
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.016
GPT teacher head0.290
Teacher spread0.274 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations26
Published2016
Admission routes1
Has abstractyes

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