Cholesterol depletion inhibits src family kinase‐dependent calcium mobilization and apoptosis induced by rituximab crosslinking
Bibliographic record
Abstract
The monoclonal antibody (mAb) rituximab produces objective clinical responses in patients with B-cell non-Hodgkin's lymphoma and antibody-based autoimmune diseases. Mechanisms mediating B-cell depletion by rituximab are not completely understood and may include direct effects of signalling via the target antigen CD20. Like most but not all CD20 mAbs, rituximab induces a sharp change in the solubility of the CD20 protein in the non-ionic detergent Triton-X-100, reflecting a dramatic increase in the innate affinity of CD20 for membrane raft signalling domains. Apoptosis induced by rituximab hypercrosslinking has been shown to require src family kinases (SFK), which are enriched in rafts. In this report we provide experimental evidence that SFK-dependent apoptotic signals induced by rituximab are raft dependent. Cholesterol depletion prevented the association of hypercrosslinked CD20 with detergent-insoluble rafts, and attenuated both calcium mobilization and apoptosis induced with rituximab. CD20 cocapped with the raft-associated transmembrane adaptor LAB/NTAL after hypercrosslinking with CD20 mAbs, regardless of their ability to induce a change in the affinity of CD20 for rafts. Taken together, the data demonstrate that CD20 hypercrosslinking via rituximab activates SFKs and downstream signalling events by clustering membrane rafts in which antibody-bound CD20 is localized in a high-affinity configuration.
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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 | 0.000 |
| 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".