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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".