Linear PADRE T Helper Epitope and Carbohydrate B Cell Epitope Conjugates Induce Specific High Titer IgG Antibody Responses
Bibliographic record
Abstract
Linear carbohydrate-peptide constructs based on the 13 amino acid nonnatural pan DR epitope (PADRE) and carbohydrate B cell epitopes are demonstrated to be potent immunogens. These data support our belief that PADRE should be considered as an alternative to more complex carriers for use in prophylaxis and therapeutic vaccines. Two model carbohydrate-PADRE glycoconjugates were used to demonstrate that PADRE could effectively provide T cell help for carbohydrate-specific Ab responses. Conjugates of PADRE covalently linked to the human milk oligosaccharide, lacto-N-fucopentose II or a dodecasaccharide derived from Salmonella typhimurium O-Ag induced high titer IgG Ab responses in mice, which were comparable to glycoconjugates employing human serum albumin (HSA) as the carrier protein. Different adjuvants, in combination with PADRE conjugates, allowed for the modulation of the isotype profile with alum supporting an IgG1 profile; QS-21 an IgG2a, 2b profile, while an alum/QS-21 mixture generated a balanced IgG1/IgG2b isotype profile. As defined by binding to synthetic glycoconjugates, dodecasaccharide-specific Abs exhibited fine specificity similar to protective polyclonal Ab responses previously reported for dodecasaccharide-protein conjugates. The same Abs bound to intact S. typhimurium cells, suggesting that biologically relevant specificities were produced. The affinity of the dodecasaccharide-specific Abs was further shown to be comparable to that of a well-characterized, high affinity monoclonal anti-carbohydrate Ab recognizing the same epitope.
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) | 0.001 | 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) | 0.002 | 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".