Priming of immune responses to hepatitis B surface antigen in young mice immunized in the presence of maternally derived antibodies
Bibliographic record
Abstract
Early vaccination is necessary to protect infants from various infectious diseases. However, this is often unsuccessful largely due to the immaturity of the neonatal immune system. Furthermore, maternally derived antibodies can interfere with active immunization. We have previously shown in young mice that immune responses against several different antigens can be improved by the addition of oligodeoxynucleotides containing immunostimulatory CpG motifs (CpG ODN). In this study we have evaluated immunization of newborn (1-7-day-old) BALB/c mice against hepatitis B surface antigen (HBsAg), with alum and/or CpG ODN, in the presence of high levels of maternal antibody against HBsAg (anti-HBs). Seroconversion rates and anti-HBs titers were compared to those induced by a HBsAg-expressing plasmid, since other studies had suggested DNA vaccines to be superior to protein vaccines in young mice with maternal antibody. HBsAg/alum/CpG ODN was superior to DNA vaccine in inducing HBsAg-specific CTL responses in young mice in the presence of maternally transferred anti-HBs antibodies. However, B cell responses to both HBsAg/alum/CpG ODN and DNA vaccines remained weak in the presence of maternally transferred anti-HBs antibodies.
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 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 | 0.000 |
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".