Identification of a Calcium Signalling Pathway of<i>S</i>-[6]-Gingerol in HuH-7 Cells
Bibliographic record
Abstract
Calcium signals in hepatocytes control cell growth, proliferation, and death. Members of the transient receptor potential (TRP) cation channel superfamily are candidate calcium influx channels. NF κ B activation strictly depends on calcium influx and often induces antiapoptotic genes favouring cell survival. Previously, we reported that S-[6]-gingerol is an efficacious agonist of the transient receptor potential cation channel subfamily V member 1 (TRPV1) in neurones. In this study, we tested the effect of S-[6]-gingerol on HuH-7 cells using the Fluo-4 calcium assay, RT-qPCR, transient cell transfection, and luciferase measurements. We found that S-[6]-gingerol induced a transient rise in [Ca(2+)] i in HuH-7 cells. The increase in [Ca(2+)] i induced by S-[6]-gingerol was abolished by preincubation with EGTA and was also inhibited by the TRPV1 channel antagonist capsazepine. Expression of TRPV1 in HuH-7 cells was confirmed by mRNA analysis as well as a test for increase of [Ca(2+)] i by TRPV1 agonist capsaicin and its inhibition by capsazepine. We found that S-[6]-gingerol induced rapid NF κ B activation through TRPV1 in HuH-7 cells. Furthermore, S-[6]-gingerol-induced NF κ B activation was dependent on the calcium gradient and TRPV1. The rapid NF κ B activation by S-[6]-gingerol was associated with an increase in mRNA levels of NF κ B-target genes: cIAP-2, XIAP, and Bcl-2 that encode antiapoptotic proteins.
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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 | 0.001 |
| 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".