Long‐term effects of tumor necrosis factor‐α treatment on insulin signaling pathway in HepG2 cells and HepG2 cells overexpressing constitutively active Akt/PKB
Bibliographic record
Abstract
Tumor necrosis factor-alpha (TNF-alpha) mediated attenuation of insulin signaling pathway is an important cause in several disorders like obesity, obesity linked diabetes mellitus. TNF-alpha actions vary depending upon concentration and time of exposure in various cells. In the present study, the effects of long-term TNF-alpha (1 ng/ml) exposure on the components of insulin signaling pathway in HepG2 and HepG2 cells overexpressing constitutively active Akt1/PKB-alpha (HepG2-CA-Akt/PKB) have been investigated. In parental HepG2 cells, TNF-alpha treatment for 24 h reduced the phosphorylation of Akt1/PKB-alpha and GSK-3beta and under these conditions cells also showed reduced insulin responsiveness in terms of Akt1/PKB-alpha and GSK-3beta phosphorylation. TNF-alpha pre-incubated HepG2-CA-Akt/PKB cells showed lower reduction in Akt1/PKB-alpha and GSK-3beta phosphorylation and insulin responsiveness after 24 h as compared to parental HepG2 cells. We report that the long-term TNF-alpha pre-incubation in both parental HepG2 and HepG2-CA-Akt/PKB-alpha cells leads to the reduction in the levels of IRS-1 without altering the levels of IRS-2. In order to understand the reason for the differential insulin resistance in both the cell types, the effect of long-term TNF-alpha treatment on the proteins upstream to Akt/PKB was investigated. TNF-alpha pre-incubation also showed reduced insulin-stimulated Tyr phosphorylation of insulin receptor (IR-beta) in both the cell types, moreover hyperphosphorylation of IRS-1 at Ser 312 residue was observed in TNF-alpha pre-incubated cells. As hyperphosphorylation of IRS-1 at Ser 312 can induce its degradation, it is possible that reduced insulin responsiveness after long-term TNF-alpha pre-incubation observed in this study is due to the decrease in IRS-1 levels.
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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) | 0.001 | 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".