Structure and compositional analysis of aluminum oxyhydroxide adsorbed pertussis vaccine
Bibliographic record
Abstract
Abstract Purpose The goal of this study was to characterize an acellular pertussis vaccine (Tdap) containing genetically modified pertussis toxin (gdPT) and TLR agonist adsorbed to AlOOH adjuvant. Methods Several analytical tools including nanoDSF, FTIR, and LD were used to examine the conformation of novel gdPT and the composition of AlOOH adjuvant formulations adsorbed to pertussis vaccine. Results DLS particle size results were 9.3 nm and 320 nm for gdPT. For pertussis toxoid (PT), the DLS particle size results were larger at ~440 nm. After adsorption to AlOOH, which was driven by the protein antigen, the size distribution ranged from 3.5 to 22 µm. Two thermal transitions were observed by DSC for gdPT at 70 °C and 102 °C. The main thermal transition was confirmed to be at 72 °C by nanoDSF. All three vaccine formulations showed one thermal transition: Tdap-AlOOH had a thermal transition of 74.6 °C, Tdap-E6020-AlOOH had a thermal transition at 74.2 °C, and Tdap-CpG-AlOOH had a thermal transition at 77.0 °C. Analysis of pertussis toxin (PTx) and gdPT was also performed by FTIR spectroscopy for the purpose of comparison. The second derivative of the FTIR spectra showed an additional feature for PTx at 1685 cm −1 compared to gdPT. The antigen’s amide I and II regions were largely unchanged after adsorption to AlOOH adjuvant as shown by FTIR, suggesting that there were no significant changes in the secondary structure. Conclusion gdPT conformation was successfully characterized using an array of analytical methods. All three Tdap formulations have similar thermal stability as shown by nanoDSF, similar size distribution as shown by LD, and similar overall secondary structure as shown by FTIR. In-line particle sizing and IR can be used as in-process characterization tools to monitor consistency of adsorbed vaccine and to confirm product identity.
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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".