Tumor necrosis factor-α induces claudin-3 upregulation in kidney tubular epithelial cells through NF-κB and CREB1
Bibliographic record
Abstract
Claudins are essential for tight junction formation and paracellular transport, and they affect key cellular events including proliferation and migration. The properties of tight junctions are dynamically modulated by a variety of inputs. We previously showed that the inflammatory cytokine tumor necrosis factor-α (TNFα), a major pathogenic factor in kidney disease, alters epithelial permeability by affecting the expression of claudin-1, -2, and -4 in kidney tubular cells. Here, we explored the effect of TNFα on claudin-3 (Cldn-3), a ubiquitous barrier-forming protein. We found that TNFα elevated Cldn-3 protein expression in tubular epithelial cells (LLC-PK1 and IMCD3) as early as 3 h post treatment. Bafilomycin A and bortezomib, inhibitors of lysosomal and proteasomes, respectively, reduced Cldn-3 degradation. However, TNFα caused a strong upregulation of Cldn-3 in the presence of bafilomycin, suggesting an effect independent from lysosomes. Blocking protein synthesis using cycloheximide prevented Cldn-3 upregulation by TNFα, verifying the contribution of de novo Cldn-3 synthesis. Indeed, TNFα elevated Cldn-3 mRNA levels at early time points. Using pharmacological inhibitors and siRNA-mediated silencing, we determined that the effect of TNFα on Cldn-3 was mediated by extracellular signal regulated kinase (ERK)-dependent activation of NF-κB and PKA-induced activation of CREB1. These two pathways were turned on by TNFα in parallel and both were required for the upregulation of Cldn-3. Because Cldn-3 was suggested to modulate cell migration and epithelial-mesenchymal transition (EMT), and TNFα was shown to affect these processes, Cldn-3 upregulation may modulate regeneration of the tubules following injury.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".