Carbohydrate-Based Ice Recrystallization Inhibitors Increase Infectivity and Thermostability of Viral Vectors
Bibliographic record
Abstract
The inability of vaccines to retain sufficient thermostability has been an obstacle to global vaccination programs. To address this major limitation, we utilized carbohydrate-based ice recrystallization inhibitors (IRIs) to eliminate the cold chain and stabilize the potency of Vaccinia virus (VV), Vesicular Stomatitis virus (VSV) and Herpes virus-1 (HSV-1). The impact of these IRIs was tested on the potency of the viral vectors using a plaque forming unit assay following room temperature storage, cryopreservation with successive freeze-thaw cycles and lyophilization. Viral potency after storage with all three conditions demonstrated that N-octyl-gluconamide (NOGlc) recovered the infectivity of shelf stored VV, 5.6 Log₁₀ PFU mL(-1) during 40 days, and HSV-1, 2.7 Log₁₀ PFU mL(-1) during 9 days. Carbon-linked antifreeze glycoprotein analogue ornithine-glycine-glycine-galactose (OGG-Gal) increases the recovery of VV and VSV more than 1 Log₁₀ PFU mL(-1) after 10 freeze-thaw cycles. In VSV, cryostorage with OGG-Gal maintains high infectivity and reduces temperature-induced aggregation of viral particles by 2 times that of the control. In total, OGG-Gal and NOGlc preserve virus potency during cryostorage. Remarkably, NOGlc has potential to eliminate the cold chain and permit room temperature storage of 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 | 0.000 | 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 | 0.001 |
| 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".