Interactions between Effector Cell Activity and Lymphokines: Implications for Recovery from Herpesvirus Infections
Bibliographic record
Abstract
The destruction of herpesvirus-infected target cells by antibody-dependent and direct cell cytotoxicity was enhanced by the presence of bovine lymphokine-containing preparations. To relate these effects to possible in vivo mechanisms of recovery, several in vitro approaches were used to measure the effects of lymphokine-containing preparations on controlling viral spread. In the first approach it was shown that in the presence of lymphokines, virus-infected cells could be killed earlier in the replication cycle by the mechanism of antibody-dependent cell cytotoxicity, thus possibly limiting spread of virus. That this was indeed the case was demonstrated by a decrease in the area of viral-induced cytopathology as well as in the total number of infected cells present. Secondly, the amount of infectious virus released was also markedly reduced in cultures incubated with lymphokines and immune peripheral blood lymphocytes as compared to cultures treated with either component alone. Finally, lymphokines caused the activation of macrophages. These results are discussed in terms of how various immune parameters may interact in a positive way so as to aid in the recovery from virus infection.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".