CpG ODN can re-direct the Th bias of established Th2 immune responses in adult and young mice
Bibliographic record
Abstract
Induction of an appropriate immune response is essential for successful immunization. For example, Th1 type immune responses are necessary for the control of intracellular infections whereas Th2 type responses are more useful for the control of extracellular infections. Immunostimulatory CpG ODN (oligonucleotides containing unmethylated cytosine and guanine dinucleotides in specific base contexts) act as potent adjuvants and have been shown to induce Th1 type immune responses with a number of different antigens. This study investigates the effect of CpG ODN on the Th bias of immune responses generated against the hepatitis B major surface antigen (HBsAg) in adult (6-8 weeks old) and young (<1 week old) BALB/c mice. It also investigates the potential of CpG DNA to reverse a pre-established Th2 response generated as an adult or as a neonate, following re-exposure to HBsAg in adult life. Both adult and young mice immunized with HBsAg/CpG ODN had a Th1 biased immune response (strong cytotoxic T-lymphocyte (CTL) induction, IgG2a>>IgG1). In contrast, mice immunized with HBsAg/alum had a Th2 type immune response (poor CTL, IgG1>>IgG2a). More importantly, when animals were immunized with HBsAg/alum and boosted with HBsAg/CpG ODN, the CpG ODN were able to re-direct the Th2 response pre-established by alum, whereas the animals receiving the primary immunization with HBsAg/CpG ODN and later boosted with HBsAg/alum maintained their Th1 bias, even after the boost with alum. These data suggest that CpG ODN have the ability to augment both humoral and cell mediated immune responses and override the Th2 bias created by alum, even in very young animals, which are known to have a Th2 biased immune system.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".