Tungsten toxicity on kidney tubular epithelial cells induces renal inflammation and M1-macrophage polarization
Bibliographic record
Abstract
Abstract Tungsten is widely used in medical, industrial, and military applications. The environmental exposure to tungsten has increased over the past several years and few studies have addressed its potential toxicity. In this study, we evaluated the effects of chronic oral tungsten exposure (100 ppm) on renal inflammation in mice. We found that 30- or 90-day tungsten exposure led to the accumulation of LAMP1-positive lysosomes in renal tubular epithelial cells. In addition, the kidneys of mice exposed to tungsten showed interstitial infiltration of leukocytes, myeloid cells, and macrophages together with increased levels of proinflammatory cytokines and p50/p65-NFkB subunits. In proximal tubule epithelial cells (HK-2) in vitro, tungsten induced a similar inflammatory status characterized by increased mRNA levels of CSF1, IL34, CXCL2 and CXCL10 and NFkB activation. Moreover, tungsten exposure slowed HK-2 cell proliferation and enhanced reactive oxygen species generation. Conditioned media from HK-2 cells treated with tungsten induced an M1-proinflammatory polarization of RAW macrophages as evidenced by increased levels of iNOS and interleukin-6 and decreased levels of the M2-antiinflammatory marker CD206. These effects were not observed when RAW cells were exposed to conditioned media from HK-2 cells treated with tungsten and supplemented with the antioxidant N-acetylcysteine (NAC). Similarly, direct tungsten exposure induced M1-proinflammatory polarization of RAW cells that was prevented by NAC co-treatment. Altogether, our data suggest that prolonged tungsten exposure leads to oxidative injury in the kidney ultimately leading to chronic renal inflammation characterized by a proinflammatory status in kidney tubular epithelial cells and immune cell infiltration.
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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) | 0.001 | 0.001 |
| 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".