Identity, Structure and Compositional Analysis of Aluminum Phosphate Adsorbed Pediatric Quadrivalent and Pentavalent Vaccines
Bibliographic record
Abstract
Abstract Purpose The goal of this study is to set an empirical baseline to map the structure-function relation of the antigens from the commercialized vaccine products. Methods To study the structural changes of protein antigens after adsorption several analytical tools including DLS, FTIR, Fluorescence, LD, and SEM have been used. Results All antigens have shown wide range of hydrodynamic diameter from 7 nm to 182 nm. Upon adjuvantation, the size distribution has become narrow, ranging from 10 to 12 μm, and has been driven by the derived diameter of aluminum phosphate (AlPO 4 ) adjuvant. Further to examine size and morphology of adsorbed antigens, SEM has been used. The SEM results have demonstrated that the AlPO 4 adjuvant suspension and adsorbed proteins consist of submicron particles that form a continuous porous surface. Diphtheria Toxoid (DT), Tetanus Toxoid (TT), and chemically-modified Filamentous Haemagglutinin (FHA) have shown surface adsorption to AlPO 4. Secondary structure alpha-helix and beta-sheet content of DT and TT has increased after adsorption to AlPO 4 adjuvant as shown by FTIR, whereas no significant changes were noted for other protein antigens. The results from Intrinsic Fluorescence have shown a structural rearrangement in DT and TT, consistent with the FTIR results. Multivalent vaccine product identity has been determined by FTIR as unique fingerprint spectrum. Conclusion The globular proteins such as DT and TT have shown changes in secondary structure upon adsorption to AlPO 4 , whereas fibrillar protein FHA has not been affected by adsorption. FTIR can be used as a lean technique to confirm product identity at different manufacturing sites.
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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".