Natural antibody recognition, signaling and surveillance in v-Ha-ras- and PKC-B1-overexpressing 10T1/2 fibroblasts
Bibliographic record
Abstract
Extensive evidence supports a role for polyclonal serum natural antibody (NAb) acting as a mediator of natural resistance against tumors in mice. However, little is known about its mechanisms of action or about the phenotype of susceptible cells. C3H 10T${1\\over 2}$ fibroblasts overexpressing an activated ras oncogene or a PKC-$\\beta$1 gene increased their NAb binding capacities, identifying PKC, an integral signaling molecule of normal cellular activation, as a key regulator of NAb binding structures. This, coupled with corresponding decreases in expression of membrane PKC-$\\alpha$ and NAb binding in resting confluent 10T${1\\over 2}$ cells raised the possibility that, in general, cells activated through PKC are NAb sensitive. In addition, NAb interaction with 10T${1\\over 2}$ variants initiated a signal transduction mechanism including activation of PKC, shedding of cell surface molecules and bound NAb, a reduction in phosphotyrosine levels of a membrane-associated 60 KDa molecule, and, over time, the inhibition of DNA synthesis. Together with the increased in vivo elimination of the high NAb binding PKC-$\\beta$1-overexpressing cells and the beneficial effect of passive syngeneic NAb in the rejection of syngeneic tumors injected s.c. and i.v. in both xid-bearing B cell deficient and B cell normal mouse models, the data argued that NAb not only participates in tumor surveillance of preneoplasia and neoplasia but contributes to homeostasis of the organism.
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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 | 0.001 |
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".