Enhancing actions of peptides derived from the γ-chain of fetal human hemoglobin on the immunostimulant activities of monophosphoryl lipid A
Bibliographic record
Abstract
Hemoglobin and its structures have been described since the 1990s to enhance a variety of biological activities of endotoxins (LPS) in a dose-dependent manner. To investigate the interaction processes in more detail, the system was extended by studying the interactions of newly designed peptides from the γ-chain of human hemoglobin with the adjuvant monophosphoryl lipid A (MPLA), a partial structure of lipid A lacking its 1-phosphate. It was found that some selected Hbg peptides, in particular two synthetic substructures designated Hbg32 and Hbg35, considerably increased the bioactivity of MPLA, which alone was only a weak activator of immune cells. These findings hold true for human mononuclar cells, monocytes and T lymphocytes. To understand the mechanisms of action in more detail, biophysical techniques were applied. These showed a peptide-induced change of the MPLA aggregate structure from multilamellar into a non-lamellar, probably inverted, cubic structure. Concomitantly, the peptides incorporated into the tightly packed MPLA aggregates into smaller units down to monomers. The fragmentation of the aggregates was an endothermic process, differing from a complex formation but rather typical for a catalytic reaction.
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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 | 0.000 |
| 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".