TENS-like Stimulation Downregulates Inflammatory Cytokines in a PC-12 Cell Line
Bibliographic record
Abstract
OBJECTIVES: The purpose of this study was to evaluate the effects of transcutaneous electrical nerve stimulation (TENS)-like stimulation on the expression of the proinflammatory cytokines tumor necrosis factor α (TNF-α), interleukin 1β (IL-1β), and IL-6 in PC-12 cells, which are commonly used as neuronal cell models. METHODS: Nerve growth factor-differentiated PC-12 cells were exposed to electrical stimulation for 15 minutes at 1 mA, 200 μs, and 100 Hz. Cell lysate from stimulated and control cells was assayed for TNF-α, IL-1β, and IL-6. In 6 trials, cells were preincubated with the L-type ion channel blocker nicardipine. Cultured cells were also incubated with Alexa Fluor 488 and visualized by fluorescence microscopy to determine the nuclear vs cytoplasmic distribution of the p65 sub-unit of NF-κB RESULTS: Compared with control (unstimulated) cells, the stimulated cells had a downregulation of the assayed cytokines. However, preincubation with the L-type ion channel blocker nicardipine blocked this effect of stimulation. Additionally, it was noted that TENS-like stimulation promoted a relative sequestration of the p65 subunit of NF-κB in the cytoplasm vs the nucleus. CONCLUSIONS: It appears that in this cell line and with these stimulation parameters, TENS-like stimulation attenuated the expression of the assayed proinflammatory cytokines, in part by promoting the relative sequestration of the p65 subunit of NF-κB in the cytoplasm, and that voltage-dependent calcium channels have a role in the cascade of events initiated by the TENS-like stimulation.
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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) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".