Characterization and Quantification of Adeno-Associated Virus Capsid-Loading States by Multi-Wavelength Analytical Ultracentrifugation with Ultrascan
Bibliographic record
Abstract
Aim: We present multi-wavelength (MW) analytical ultracentrifugation (AUC) methods offering superior accuracy for adeno-associated virus characterization and quantification. Methods: Experimental design guidelines are presented for MW sedimentation velocity and analytical buoyant density equilibrium AUC. Results: Our results were compared with dual-wavelength AUC, transmission electron microscopy and mass photometry. In contrast to dual-wavelength AUC, MW-AUC correctly quantifies adeno-associated virus capsid ratios and identifies contaminants. In contrast to transmission electron microscopy, partially filled capsids can also be detected and quantified. In contrast to mass photometry, first-principle results are obtained. Conclusion: Our study demonstrates the improved information provided by MW-AUC, highlighting the utility of several recently integrated UltraScan programs, and reinforces AUC as the gold-standard analysis for viral vectors.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".