Differential role of reactive oxygen species in the activation of mitogen‐activated protein kinases and Akt by key receptors on B‐lymphocytes: CD40, the B cell antigen receptor, and CXCR4
Bibliographic record
Abstract
BACKGROUND: Antibodies produced by B-lymphocytes play a key role in the host defense against infection. The development, survival, and activation of B cell is regulated by multiple receptors including the B cell antigen receptor (BCR), which detects the presence of pathogens, CD40, which binds co-stimulatory molecules on activated T cells, and chemokines such as SDF-1 (CXCL12) that play key roles in B cell development and trafficking. Signaling by many receptors results in the generation of reactive oxygen species (ROS) that function as second messengers by regulating the activity of redox-sensitive kinases and phosphatases. We investigated the role of ROS in signaling by the BCR, CD40, and CXCR4, the receptor for SDF-1. We focused on activation of ERK, JNK, p38, and Akt, kinases that regulate multiple processes including cell survival, proliferation, and migration. RESULTS: Using the anti-oxidants N-acetyl L-cysteine (NAC) and ebselen to deplete intracellular ROS, we identified a differential requirement for ROS in the activation of ERK, JNK, p38, and Akt by these receptors. We found that CD40 activated JNK, p38, and Akt via redox-dependent pathways that were sensitive to ROS depletion by NAC and ebselen. In contrast, BCR-induced activation of ERK, JNK, p38, and Akt was not affected by ROS depletion. We also found that CXCR4-induced Akt activation was ROS-dependent even though activation of the ERK, JNK, and p38 MAP kinases by CXCR4 occurred via ROS-independent pathways. CONCLUSION: The differential requirement for ROS in the activation of ERK, JNK, p38, and Akt by the BCR, CD40, and CXCR4 likely reflects the multiplicity of upstream activators for each of these kinases, only some of which may be regulated in a redox-dependent manner. These findings support the idea that ROS are important second messengers in B cells and suggest that oxidants or anti-oxidants could be used to modulate B cell activation.
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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) | 0.002 | 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".