Lymphoma cells contribute to the augmentation of plasma sL-selectins in the serum of lymphoma-bearing mice
Bibliographic record
Abstract
Like many integral membrane glycoproteins, the extracellular domain of L-selectin undergoes rapid shedding, which occurs on both resting and activated host leucocytes. Incubating normal or transformed leukocytes with phorbol esters can also artificially induce shedding of L-selectin, providing multiple possibilities for the source of soluble forms of L-selectin found in the serum of patients with hematological malignancies. Here, using genetically engineered L-selectin-deficient mouse models, we have measured the release of soluble circulating forms of L-selectin in the serum of lymphoma-bearing mice. We found that L-selectin-deficient lymphoma cells could not induce an elevation of circulating soluble forms of L-selectin in normal mice, as compared to lymphoma cells expressing L-selectin. Moreover, soluble forms of L-selectin were detected in the serum in mice bearing lymphoma induced by injection of T lymphoma cells expressing L-selectins. Interestingly, we also found that lymphoma cells that are unable to shed L-selectin in vitro following exposure to phorbol ester can generate soluble forms of serum L-selectin in vivo. Taken together, these results indicate that lymphoma cells are the major contributors to levels of soluble forms of L-selectins in lymphoma-bearing mice.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".