NF-κB signaling maintains the survival of cadmium-exposed human renal glomerular endothelial cells
Bibliographic record
Abstract
The kidney is one of the primary organs targeted by cadmium (Cd), a widely distributed environmental pollutant. The glomerular endothelium is the major component of the glomerular filtration barrier. However, the effects of Cd on glomerular endothelial cells remain largely unknown. For this purpose, we aimed to determine the effects of low dose Cd on the survival of human renal glomerular endothelial cells (HRGECs). Cultured HRGECs were exposed to 4 µM cadmium chloride (CdCl2) and examined at different time-points. We found that Cd activates the nuclear factor-κB (NF-κB) pathway without inducing the apoptosis of HRGECs. Pre-treating the cells with pyrrolidine dithiocarbamate (PDTC), a potent NF-κB inhibitor, prior to Cd exposure triggered extensive cell death (73.5%). In addition, Cd activates the c-Jun N-terminal kinase (JNK) pathway, and inhibition of the NF-κB pathway significantly elevates Cd-induced JNK phosphorylation in HRGECs (p<0.01). The combination treatment of PDTC and SP600125, a JNK pathway inhibitor, increased the survival of Cd-stimulated HRGECs compared with those cells treated with PDTC alone (p<0.05). Taken together, these findings demonstrate that the NF-κB pathway plays an essential role in maintaining the survival of Cd-exposed HRGECs.
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".