Cell death and DNA damage in peritoneal macrophages of mice (Mus musculus) exposed to inorganic lead
Bibliographic record
Abstract
Lead is a heavy metal of considerable environmental and occupational concern and there is growing evidence that it is toxic to the human immune system. In this regard, this study examined the effect of lead (Pb) exposure to peritoneal macrophages (Mvarphis) of mice (Mus musculus) cultivated in DMEM medium supplemented with fetal bovine serum, in order to investigate cell damage related to cell death. Cells were exposed to two concentrations of inorganic lead [Pb(II)] for 4, 24 and 72h. Cell viability declined during the treatment, with responses including cell death, cellular damage and DNA damage. Cell death images were found in treated cells with an increase in Bax expression, but the inorganic lead failed to induce the loss of membrane asymmetry (Annexin V conjugates), suggesting that cell death was mainly due to necrosis induction. The effects of Pb(II) on the mechanisms of cell death is not completely understood, but the immunosuppression due to DNA damage and Mvarphis death is discussed here. We have previously shown the effect of inorganic lead in mitochondria and phagocytosis in Mvarphis, suggesting here a pathway for the effect of the metal on mechanisms of cell death, also discussing its effects on the immune system.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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".