Silica particles cause NADPH oxidase–independent ROS generation and transient phagolysosomal leakage
Bibliographic record
Abstract
Chronic inhalation of silica particles causes lung fibrosis and silicosis. Silica taken up by alveolar macrophages causes phagolysosomal membrane damage and leakage of lysosomal material into the cytoplasm to initiate apoptosis. We investigated the role of reactive oxygen species (ROS) in this membrane damage by studying the spatiotemporal generation of ROS. In macrophages, ROS generated by NADPH oxidase 2 (NOX2) was detected in phagolysosomes containing either silica particles or nontoxic latex particles. ROS was only detected in the cytoplasm of cells treated with silica and appeared in parallel with an increase in phagosomal ROS, as well as several hours later associated with mitochondrial production of ROS late in apoptosis. Pharmacological inhibition of NOX activity did not prevent silica-induced phagolysosomal leakage but delayed it. In Cos7 cells, which do not express NOX2, ROS was detected in silica-containing phagolysosomes that leaked. ROS was not detected in phagolysosomes containing latex particles. Leakage of silica-containing phagolysosomes in both cell types was transient, and after resealing of the membrane, endolysosomal fusion continued. These results demonstrate that silica particles can generate phagosomal ROS independent of NOX activity, and we propose that this silica-generated ROS can cause phagolysosomal leakage to initiate apoptosis.
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 | 0.000 | 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".