A simple macroscopic model for the diffusion and adsorption kinetics of r‐adenovirus
Bibliographic record
Abstract
The diffusion of viruses toward cells is a limiting step of the infection process. To be modeled correctly, this step must be evaluated in combination with the adsorption of the virus to the cell surface, which is a rapid but reversible step. In this paper, the recombinant adenovirus (rAd) diffusion and its adsorption to 293S cells in suspension were both measured and modeled. First, equilibrium experiments permitted to determine the number of receptors on the surface of 293S (R(T) = 3,500 cell(-1)) and the association constant (K(A) = 1.9 x 10(11) M(-1)) for rAd on these cells based on a simple monovalent adsorption model. Non-specific binding of the virus to the cell surface was not found to be significant. Second, total virus particle degradation rates between 5.2 x 10(-3) and 4.0 x 10(-2) min(-1) were measured at 37 degrees C in culture medium, but no significant virus degradation was observed at 4 degrees C. Third, free viral particle disappearance rates from a mixed suspension of virus and cells were measured at different virus concentrations. Experimental data were compared to a phenomenological dynamic model comprising both the diffusion and the adsorption steps. The diffusion to adsorption ratio, a fitted parameter, confirmed that the contact process of a virus with a cell is indeed diffusion controlled. However, the characteristic diffusion time constants obtained, based on a reversible adsorption model, were eightfolds smaller than those reported in the literature, based on diffusion models that assume irreversible adsorption.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".