Effects of protein–protein interaction in ultrafiltration based fractionation processes
Bibliographic record
Abstract
This paper discusses the use of pulsed sample injection ultrafiltration (UF) for investigating protein-protein interaction, particularly its effect on protein transmission through UF membranes. Several binary protein mixtures were investigated; the proteins in each mixture being selected such that one of the proteins in the pair would be preferentially transmitted while the other would be either totally or substantially retained. The "retained" protein either decreased or increased or did not affect the sieving coefficient of the "transmitted" protein, this depending the type of protein-protein interaction, that is, associative, repulsive, or neutral. The type of protein-protein interaction depended on the particular protein pair under investigation as well as on the operating conditions used (pH and salt concentration). The magnitude of either decrease or increase in transmission of a preferentially transmitted protein due to the presence of a retained protein was found to be independent of the manner in which the proteins were injected into the system, that is, simultaneous or sequential. These magnitudes however correlated well with the ratio of the two proteins present in the feed.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".