Mechanisms involved in methylmercuric chloride (MeHgCl)-induced suppression of human neutrophil apoptosis
Bibliographic record
Abstract
We have previously demonstrated that concentrations of 1-10 microM of methylmercuric chloride (MeHgCl) that are cytotoxic to monocytes-macrophages can curiously inhibit neutrophil apoptosis by a yet unknown mechanism. In the present study, we demonstrate that, as with the cytokine granulocyte-macrophage colony-stimulating factor (GM-CSF), a classical inhibitor of neutrophil apoptosis, treatment of cells with 5 microM MeHgCl induces de novo protein synthesis and prevents the loss of expression of the antiapoptotic Mcl-1 protein. The expression of the cytoskeletal proteins gelsolin, paxillin and vinculin was similar in MeHgCl- or GM-CSF-induced suppression of apoptosis. However, MeHgCl prevents the degradation of vimentin differently than GM-CSF. Apoptosis was further confirmed by flow cytometry (FITC annexin-V), and by monitoring CD16 cell surface expression. Curiously, unlike GM-CSF, MeHgCl did not prevent CD16 shedding. We conclude that, like GM-CSF, MeHgCl can delay neutrophil apoptosis by inducing de novo protein synthesis and by preventing the loss of the antiapoptotic Mcl-1 protein. However, unlike GM-CSF, MeHgCl induces an atypical degradation of vimentin without preventing CD16 shedding.
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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".